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Masters Degrees (Mathematical Modeling)

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Complex systems with a technological, biological or socio-economic background determine our everyday life. Read more

About the Program

Complex systems with a technological, biological or socio-economic background determine our everyday life. The challenge of modeling these complex systems mathematically demands the following prototypic profile of an "expert mastering a repertoire of modern mathematical and computer based methods for modeling, simulating and optimizing complex systems and knowing how to combine those methods for solving real-world problems".
The term expert is understood in the sense of generalist and not a specialist, since this program aims at teaching a broad spectrum of modern methods.

The two-years English-taught master program "Mathematical Modeling of Complex Systems" focuses on advanced techniques of modeling, simulation and optimization. A substantial set of elective courses allows concentration on areas of individual interest. A mobility window enables the students to study abroad and gain scientific and cultural experience at international partner universities. This program uses English as medium of instruction since its graduates will enter a highly globalized work and research community. Besides that, the participation and enrollment of international candidates is explicitly welcomed.

Application oriented, interdisciplinary seminars link the theoretical basics and concepts of modeling and simulation. Students work in small teams to solve real world problems. This teamwork reflects typical work in applied sciences and corresponds to our paradigm of an "expert mastering a repertoire of methods to solve problems".

Find out more about the program and our campus in Koblenz under:
https://www.uni-koblenz-landau.de/de/koblenz/fb3/mathe/studium/mmcs/

Aims/Career Perspectives

The Master degree in Mathematical Modeling of Complex Systems is to give those possessing extended skills in Mathematics, Physics and Computer Science in theory, experiment and practical application. These skills are complemented with further knowledge in additional topics, individually selected by each student. The degree entitles its holder to exercise professional work in the field of Applied Mathematics and/or Mathematical Modeling in science or industry or to pursue a PhD program in related fields.

Program Structure

The first three terms of the two-years master „Mathematical Modeling of Complex Systems“ consist of core courses in Applied Mathematics and Applied Physics. Elective courses in Applied Mathematics, Applied Physics and Computer Sciences allow each student to set its individual focus. Active use of the gained knowledge and its application to the solution of real-world problems is taught and practiced in a project seminar. This project seminar can be carried out in a three-month period at a research institution, enterprise or at university. The master thesis in the last term and dealing with modeling and simulating a real-world problem, shows the student’s ability to perform independent research work.
The core and elective courses typically include a written or oral exam, the project seminar is graded based an oral presentation and written report of the project results.

You can find an exemplary list of courses and can download a overview of the modules under:
https://www.uni-koblenz-landau.de/de/koblenz/fb3/mathe/studium/mmcs#curriculum

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The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. Read more

Mathematical Biology at Dundee

The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. In his famous book On Growth and Form (where he applied geometric principles to morphological problems) Thompson declares:

"Cell and tissue, shell and bone, leaf and flower, are so many portions of matter, and it is in obedience to the laws of physics that their particles have been moved, molded and conformed. They are no exceptions to the rule that God always geometrizes. Their problems of form are in the first instance mathematical problems, their problems of growth are essentially physical problems, and the morphologist is, ipso facto, a student of physical science."

Current mathematical biology research in Dundee continues in the spirit of D'Arcy Thompson with the application of modern applied mathematics and computational modelling to a range of biological processes involving many different but inter-connected phenomena that occur at different spatial and temporal scales. Specific areas of application are to cancer growth and treatment, ecological models, fungal growth and biofilms. The overall common theme of all the mathematical biology research may be termed"multi-scale mathematical modelling" or, from a biological perspective, "quantitative systems biology" or"quantitative integrative biology".

The Mathematical Biology Research Group currently consists of Professor Mark Chaplain, Dr. Fordyce Davidson and Dr. Paul Macklin along with post-doctoral research assistants and PhD students. Professor Ping Lin provides expertise in the area of computational numerical analysis. The group will shortly be augmented by the arrival of a new Chair in Mathematical Biology (a joint Mathematics/Life Sciences appointment).

As a result, the students will benefit directly not only from the scientific expertise of the above internationally recognized researchers, but also through a wide-range of research activities such as journal clubs and research seminars.

Aims of the programme

1. To provide a Masters-level postgraduate education in the knowledge, skills and understanding of mathematical biology.
2. To enhance analytical and critical abilities and competence in the application of mathematical modeling techniques to problems in biomedicine.

Prramme Content

This one year course involves taking four taught modules in semester 1 (September-December), followed by a further 4 taught modules in semester 2 (January-May), and undertaking a project over the Summer (May-August).

A typical selection of taught modules would be:

Dynamical Systems
Computational Modelling
Statistics & Stochastic Models
Inverse Problems
Mathematical Oncology
Mathematical Ecology & Epidemiology
Mathematical Physiology
Personal Transferable Skills

Finally, all students will undertake a Personal Research Project under the supervision of a member of staff in the Mathematical Biology Research Group.

Methods of Teaching

The programme will involve a variety of teaching formats including lectures, tutorials, seminars, journal clubs, case studies, coursework, and an individual research project.

Taught sessions will be supported by individual reading and study.

Students will be guided to prepare their research project plan and to develop skills and competence in research including project management, critical thinking and problem solving, project reporting and presentation.

Career Prospects

The Biomedical Sciences are now recognizing the need for quantitative, predictive approaches to their traditional qualitative subject areas. Healthcare and Biotechnology are still fast-growing industries in UK, Europe and Worldwide. New start-up companies and large-scale government investment are also opening up employment prospects in emerging economies such as Singapore, China and India.

Students graduating from this programme would be very well placed to take advantage of these global opportunities.

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In recent years, biological research has become increasingly interdisciplinary, focusing heavily on mathematical modeling and on the analysis of system-wide quantitative information. Read more

Computational Life Science

In recent years, biological research has become increasingly interdisciplinary, focusing heavily on mathematical modeling and on the analysis of system-wide quantitative information. Sophisticated high-throughput techniques pose new challenges for data integration and data interpretation. The Computational Life Science (CompLife) MSc program at Jacobs University meets these challenges by covering computational, theoretical and mathematical approaches in biology and the life sciences. It is geared towards students of bioinformatics, computer science, physics, mathematics and related areas.

Program Features

The CompLife program is located at Jacobs University, a private and international English-language academic institution in Bremen, Germany. CompLife students at Jacobs University take a tailor-made curriculum comprising lectures, seminars and laboratory trainings. Courses cover foundational as well as advanced topics and methods. Core components of the program and areas of specialization include:

- Computational Systems Biology
- Computational Physics and Biophysics
- Bioinformatics
- RNA Biology
- Imaging and Modeling in Medicine
- Ecological Modeling
- Theoretical Biology
- Applied Mathematics
- Numerical Methods

For more details on the CompLife curriculum, please visit the program website at http://www.jacobs-university.de/complife.

Career Options

Graduates of the CompLife program are prepared for a career in biotechnology and biomedicine. Likewise, graduates of the program are qualified to move on to a PhD.

Application and Admission

The CompLife program starts in the first week of September every year. Please visit http://www.jacobs-university.de/graduate-admission or use the contact form to request details on how to apply. We are looking forward to receiving your inquiry.

Scholarships and Funding Options

All applicants are automatically considered for merit-based scholarships of up to € 12,000 per year. Depending on availability, additional scholarships sponsored by external partners are offered to highly gifted students. Moreover, each admitted candidate may request an individual financial package offer with attractive funding options. Please visit http://www.jacobs-university.de/study/graduate/fees-finances to learn more.

Campus Life and Accommodation

Jacobs University’s green and tree-shaded campus provides much more than buildings for teaching and research. It is home to an intercultural community which is unprecedented in Europe. A Student Activities Center, various sports facilities, a music studio, a student-run café/bar, concert venues and our Interfaith House ensure that you will always have something interesting to do.

For graduate students who would like to live on campus, Jacobs University offers accommodation in four residential colleges. Each college has its own dining room, recreational lounge, study areas, and common and group meeting rooms. Please visit http://www.jacobs-university.de/study/graduate/campus-life for more information.

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EMARO+ is an integrated Masters course conducted by. Ecole Centrale de Nantes (France), Warsaw University of Technology (Poland), the University of Genoa (Italy), and Jaume I University (Spain). Read more
EMARO+ is an integrated Masters course conducted by: Ecole Centrale de Nantes (France), Warsaw University of Technology (Poland), the University of Genoa (Italy), and Jaume I University (Spain).

It has been designed and accepted in the framework of the European Union ERASMUS-MUNDUS programme (ERASMUS+ H2020).

It has 7 associated partners: two Asian Institutions (KEIO University - Japan, SJTU - China) and five industrial partners (IRT Jules Verne - France, Airbus Group Innovations - France), BA Systemes - France, Robotnik - Spain, and SIIT - Italy).

The programme of study lasts two academic years (120 ECTS) split into four equally loaded semesters. The student has to spend the first two semesters in one European institution and the second two semesters in another European institution. Another mobility during the fourth semester to an Asian partner or to an industrial partner is possible.

The language of instruction is English, but local language and culture courses of the hosting countries are included in the programme of study. The aim of the first two semesters is to provide the students with a solid interdisciplinary background across the main areas of robotics (Cognition, Action, Perception). During the third semester, depending on the host institution, the student will deal with one or more of the following sectors: industrial robot systems, service robots (domestic, health, rehabilitation, leisure), intelligent vehicules and security robots. The fourth semester is dedicated to the Masters Thesis. The student carries out his/her research work under the joint supervision of two advisors from two different consortium institutions.

Students that graduate from the EMARO masters course obtain two masters degrees from the European institutions where they studied. The obtained degrees are officially recognised and give full access to PhD study programmes.

The Consortium delivers a Diploma supplement describing the nature, level, context, content and status of the studies that were pursued and successfully completed by the student.

The Masters is designed to promote a high-quality educational offer in the area of advanced and intelligent robotics. After graduation the students will have mastered the different areas of robotics (Mathematical modeling, Control Engineering, Computer Engineering, Mechanical design) in order to be able to deal with Robotics systems as a whole rather than just to concentrate on one particular area.

Although the EMARO+ programme is applied primarily within the context of robotic systems, the concepts covered can be applied to a much wider range of other engineering and economical systems. The career prospects for EMARO+ graduates are therefore excellent. They can be employed in many industrial and economical companies, as the courses are relevant to today’s high technology society.

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The Department of Metallurgical and Materials Engineering offers a master of science in metallurgical engineering. Visit the website http://mte.eng.ua.edu/graduate/ms-program/. Read more
The Department of Metallurgical and Materials Engineering offers a master of science in metallurgical engineering.

Visit the website http://mte.eng.ua.edu/graduate/ms-program/

The program options include coursework only or by a combination of coursework and approved thesis work. Most on-campus students supported on assistantships are expected to complete an approved thesis on a research topic.

Plan I is the standard master’s degree plan. However, in exceptional cases, a student who has the approval of his or her supervisory committee may follow Plan II. A student who believes there are valid reasons for using Plan II must submit a written request detailing these reasons to the department head no later than midterm of the first semester in residence.

All graduate students, during the first part and the last part of their programs, will be required to satisfactorily complete MTE 595/MTE 596. This hour of required credit is in addition to the other degree requirements.

Course Descriptions

MTE 519 Principles of Casting and Solidification Processing. Three hours.
Overview of the principles of solidification processing, the evolution of solidification microstructure, segregation, and defects, and the use of analytical and computational tools for the design, understanding, and use of solidification processes.

MTE 520 Simulation of Casting Processes Three hours.
This course will cover the rationale and approach of numerical simulation techniques, casting simulation and casting process design, and specifically the prediction of solidification, mold filling, microstructure, shrinkage, microporosity, distortion and hot tearing. Students will learn casting simulation through lectures and hands-on laboratory/tutorial sessions.

MTE 539 Metallurgy of Welding. Three hours.
Prerequisite: MTE 380 or permission of the instructor.
Thermal, chemical, and mechanical aspects of welding using the fusion welding process. The metallurgical aspects of welding, including microstructure and properties of the weld, are also covered. Various topics on recent trends in welding research.

MTE 542 Magnetic Recording Media. Three hours.
Prerequisite: MTE 271.
Basic ferromagnetism, preparation and properties of magnetic recording materials, magnetic particles, thin magnetic films, soft and hard film media, multilayered magnetoresistive media, and magneto-optical disk media.

MTE 546 Macroscopic Transport in Materials Processing. Three hours.
Prerequisite: MTE 353 or permission of the instructor.
Elements of laminar and turbulent flow; heat transfer by conduction, convection, and radiation; and mass transfer in laminar and in turbulent flow; mathematical modeling of transport phenomena in metallurgical systems including melting and refining processes, solidification processes, packed bed systems, and fluidized bed systems.

MTE 547 Intro to Comp Mat. Science Three hours.
This course introduces computational techniques for simulating materials. It covers principles of quantum and statistical mechanics, modeling strategies and formulation of various aspects of materials structure, and solution techniques with particular reference to Monte Carlo and Molecular Dynamic methods.

MTE 549 Powder Metallurgy. Three hours.
Prerequisite: MTE 380 or permission of the instructor.
Describing the various types of powder processing and how these affect properties of the components made. Current issues in the subject area from high-production to nanomaterials will be discussed.

MTE 550 Plasma Processing of Thin Films: Basics and Applications. Three hours.
Prerequisite: By permission of instructor.
Fundamental physics and materials science of plasma processes for thin film deposition and etch are covered. Topics include evaporation, sputtering (special emphasis), ion beam deposition, chemical vapor deposition, and reactive ion etching. Applications to semiconductor devices, displays, and data storage are discussed.

MTE 556 Advanced Mechanical Behavior of Materials I: Strengthening Methods in Solids. Three hours. Same as AEM 556.
Prerequisite: MTE 455 or permission of the instructor.
Topics include elementary elasticity, plasticity, and dislocation theory; strengthening by dislocation substructure, and solid solution strengthening; precipitation and dispersion strengthening; fiber reinforcement; martensitic strengthening; grain-size strengthening; order hardening; dual phase microstructures, etc.

MTE 562 Metallurgical Thermodynamics. Three hours.
Prerequisite: MTE 362 or permission of instructor.
Laws of thermodynamics, equilibria, chemical potentials and equilibria in heterogeneous systems, activity functions, chemical reactions, phase diagrams, and electrochemical equilibria; thermodynamic models and computations; and application to metallurgical processes.

MTE 574 Phase Transformation in Solids. Three hours.
Prerequisites: MTE 373 and or permission of the instructor.
Topics include applied thermodynamics, nucleation theory, diffusional growth, and precipitation.

MTE 579 Advanced Physical Metallurgy. Three hours.
Prerequisite: Permission of the instructor.
Graduate-level treatments of the fundamentals of symmetry, crystallography, crystal structures, defects in crystals (including dislocation theory), and atomic diffusion.

MTE 583 Advanced Structure of Metals. Three hours.
Prerequisite: Permission of the instructor.
The use of X-ray analysis for the study of single crystals and deformation texture of polycrystalline materials.

MTE 585 Materials at Elevated Temperatures. Three hours.
Prerequisite: Permission of the instructor.
Influence of temperatures on behavior and properties of materials.

MTE 587 Corrosion Science and Engineering. Three hours.
Prerequisite: MTE 271 and CH 102 or permission of the instructor.
Fundamental causes of corrosion problems and failures. Emphasis is placed on tools and knowledge necessary for predicting corrosion, measuring corrosion rates, and combining this with prevention and materials selection.

MTE 591:592 Special Problems (Area). One to three hours.
Advanced work of an investigative nature. Credit awarded is based on the work accomplished.

MTE 595:596 Seminar. One hour.
Discussion of current advances and research in metallurgical engineering; presented by graduate students and the staff.

MTE 598 Research Not Related to Thesis. One to six hours.

MTE 599 Master's Thesis Research. One to twelve hours. Pass/fail.

MTE 622 Solidification Processes and Microstructures Three hours.
Prerequisite: MTE 519
This course will cover the fundamentals of microstructure formation and microstructure control during the solidification of alloys and composites.

MTE 643 Magnetic Recording. Three hours.
Prerequisite: ECE 341 or MTE 271.
Static magnetic fields; inductive head fields; playback process in recording; recording process; recording noise; and MR heads.

MTE 644 Optical Data Storage. Three hours.
Prerequisite: ECE 341 or MTE 271.
Characteristics of optical disk systems; read-only (CD-ROM) systems; write-once (WORM) disks; erasable disks; M-O recording materials; optical heads; laser diodes; focus and tracking servos; and signal channels.

MTE 655 Electron Microscopy of Materials. One to four hours.
Prerequisite: MTE 481 or permission of the instructor.
Topics include basic principles of operation of the transmission electron microscope, principles of electron diffraction, image interpretation, and various analytical electron-microscopy techniques as they apply to crystalline materials.

MTE 670 Scanning Electron Microscopy. Three hours
Theory, construction, and operation of the scanning electron microscope. Both imaging and x-ray spectroscopy are covered. Emphasis is placed on application and uses in metallurgical engineering and materials-related fields.

MTE 680 Advanced Phase Diagrams. Three hours.
Prerequisite: MTE 362 or permission of the instructor.
Advanced phase studies of binary, ternary, and more complex systems; experimental methods of construction and interpretation.

MTE 684 Fundamentals of Solid State Engineering. Three hours.
Prerequisite: Modern physics, physics with calculus, or by permission of the instructor.
Fundamentals of solid state physics and quantum mechanics are covered to explain the physical principles underlying the design and operation of semiconductor devices. The second part covers applications to semiconductor microdevices and nanodevices such as diodes, transistors, lasers, and photodetectors incorporating quantum structures.

MTE 691:692 Special Problems (Area). One to six hours.
Credit awarded is based on the amount of work undertaken.

MTE 693 Selected Topics (Area). One to six hours.
Topics of current research in thermodynamics of melts, phase equilibra, computer modeling of solidification, electrodynamics of molten metals, corrosion phenomena, microstructural evolution, and specialized alloy systems, nanomaterials, fuel cells, and composite materials.

MTE 694 Special Project. One to six hours.
Proposing, planning, executing, and presenting the results of an individual project.

MTE 695:696 Seminar. One hour.
Presentations on dissertation-related research or on items of current interest in materials and metallurgical engineering.

MTE 698 Research Not Related to Dissertation. One to six hours.

MTE 699 Doctoral Dissertation Research. Three to twelve hours. Pass/Fail.

Find out how to apply here - http://graduate.ua.edu/prospects/application/

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Joining the Department as a postgraduate is certainly a good move. The Department maintains strong research in both pure and applied mathematics, as well as the traditional core of a mathematics department. Read more
Joining the Department as a postgraduate is certainly a good move. The Department maintains strong research in both pure and applied mathematics, as well as the traditional core of a mathematics department. What makes our Department different is the equally strong research in fluid mechanics, scientific computation and statistics.

The quality of research at the postgraduate level is reflected in the scholarly achievements of faculty members, many of whom are recognized as leading authorities in their fields. Research programs often involve collaboration with scholars at an international level, especially in the European, North American and Chinese universities. Renowned academics also take part in the Department's regular colloquia and seminars. The faculty comprises several groups: Pure Mathematics, Applied Mathematics, Probability and Statistics.

Mathematics permeates almost every discipline of science and technology. We believe our comprehensive approach enables inspiring interaction among different faculty members and helps generate new mathematical tools to meet the scientific and technological challenges facing our fast-changing world.

The MPhil program seeks to strengthen students' general background in mathematics and mathematical sciences, and to expose students to the environment and scope of mathematical research. Submission and successful defense of a thesis based on original research are required.

Research Foci

Algebra and Number Theory
The theory of Lie groups, Lie algebras and their representations play an important role in many of the recent development in mathematics and in the interaction of mathematics with physics. Our research includes representation theory of reductive groups, Kac-Moody algebras, quantum groups, and conformal field theory. Number theory has a long and distinguished history, and the concepts and problems relating to the theory have been instrumental in the foundation of a large part of mathematics. Number theory has flourished in recent years, as made evident by the proof of Fermat's Last Theorem. Our research specializes in automorphic forms.

Analysis and Differential Equations
The analysis of real and complex functions plays a fundamental role in mathematics. This is a classical yet still vibrant subject that has a wide range of applications. Differential equations are used to describe many scientific, engineering and economic problems. The theoretical and numerical study of such equations is crucial in understanding and solving problems. Our research areas include complex analysis, exponential asymptotics, functional analysis, nonlinear equations and dynamical systems, and integrable systems.

Geometry and Topology
Geometry and topology provide an essential language describing all kinds of structures in Nature. The subject has been vastly enriched by close interaction with other mathematical fields and with fields of science such as physics, astronomy and mechanics. The result has led to great advances in the subject, as highlighted by the proof of the Poincaré conjecture. Active research areas in the Department include algebraic geometry, differential geometry, low-dimensional topology, equivariant topology, combinatorial topology, and geometrical structures in mathematical physics.

Numerical Analysis
The focus is on the development of advance algorithms and efficient computational schemes. Current research areas include: parallel algorithms, heterogeneous network computing, graph theory, image processing, computational fluid dynamics, singular problems, adaptive grid method, rarefied flow simulations.

Applied Sciences
The applications of mathematics to interdisciplinary science areas include: material science, multiscale modeling, mutliphase flows, evolutionary genetics, environmental science, numerical weather prediction, ocean and coastal modeling, astrophysics and space science.

Probability and Statistics
Statistics, the science of collecting, analyzing, interpreting, and presenting data, is an essential tool in a wide variety of academic disciplines as well as for business, government, medicine and industry. Our research is conducted in four categories. Time Series and Dependent Data: inference from nonstationarity, nonlinearity, long-memory behavior, and continuous time models. Resampling Methodology: block bootstrap, bootstrap for censored data, and Edgeworth and saddle point approximations. Stochastic Processes and Stochastic Analysis: filtering, diffusion and Markov processes, and stochastic approximation and control. Survival Analysis: survival function and errors in variables for general linear models. Probability current research includes limit theory.

Financial Mathematics
This is one of the fastest growing research fields in applied mathematics. International banking and financial firms around the globe are hiring science PhDs who can use advanced analytical and numerical techniques to price financial derivatives and manage portfolio risks. The trend has been accelerating in recent years on numerous fronts, driven both by substantial theoretical advances as well as by a practical need in the industry to develop effective methods to price and hedge increasingly complex financial instruments. Current research areas include pricing models for exotic options, the development of pricing algorithms for complex financial derivatives, credit derivatives, risk management, stochastic analysis of interest rates and related models.

Facilities

The Department enjoys a range of up-to-date facilities and equipment for teaching and research purposes. It has two computer laboratories and a Math Support Center equipped with 100 desktop computers for undergraduate and postgraduate students. The Department also provides an electronic homework system and a storage cloud system to enhance teaching and learning.

To assist computations that require a large amount of processing power in the research area of scientific computation, a High Performance Computing (HPC) laboratory equipped with more than 200 high-speed workstations and servers has been set up. With advanced parallel computing technologies, these powerful computers are capable of delivering 17.2 TFLOPS processing power to solve computationally intensive problems in our innovative research projects. Such equipment helps our faculty and postgraduate students to stay at the forefront of their fields. Research projects in areas such as astrophysics, computational fluid dynamics, financial mathematics, mathematical modeling and simulation in materials science, molecular simulation, numerical ocean modeling, numerical weather prediction and numerical methods for micromagnetics simulations all benefit from our powerful computing facilities.

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There is a growing concern for environmental conservation and sustainable development across the globe. To achieve long-term environmental sustainability, it requires innovative solutions to many problems caused by human. Read more
There is a growing concern for environmental conservation and sustainable development across the globe. To achieve long-term environmental sustainability, it requires innovative solutions to many problems caused by human. These problems include the presence of micropollutants in drinking water, noxious aerosols and fumes in the air, heavy metals and toxic organics in solid wastes that will eventually overwhelm our landfill sites. The scarcity of water resources, the ever-deteriorating air quality in many metropolises, the threat of mounting volumes of waste without suitable disposal sites, and a long list of other critical issues must be resolved through the innovations of scientists and engineers.

Environmental problems are essentially interdisciplinary issues. These issues include the physical process of mixing and dilution, chemical and biological processes, mathematical modeling, data acquisition and measurement. The Environmental Engineering (EVNG) Program offered by the School of Engineering at the Hong Kong University of Science and Technology (HKUST) is one of the most successful interdisciplinary research programs in this field of study. The faculty members are leading experts committed to innovative research in a broad range of environmental engineering areas. The Environmental Engineering Program offers a comprehensive curriculum that provides a solid foundation on which students may build careers in research.

The MPhil program seeks to strengthen students’ knowledge of environmental engineering and to expose them to issues in environmental pollution and conservation, and sustainable development. Students are required to undertake coursework and successfully complete a thesis to demonstrate competence in research.

Research Foci

The program focuses on innovative technologies for different applications in the environmental engineering area and seeks to provide research students with an understanding of effective environmental management strategies.

The main research areas include:
-Innovative Water and Wastewater Treatment Technologies
-Solid/Hazardous Waste Management and Waste Recycling/Reuse
-Contaminated Land and Groundwater Remediation
-Indoor and Outdoor Air Quality
-Environmental Sustainability and Renewable Energy

Facilities

The facilities of the Environmental Engineering Laboratories are divided into standard instruments and advanced stationary equipment, as required for different environmental studies. Standard instruments can provide accurate measurements of routine environmental analyses, such as DO, pH, COD, BOD5, ORP, salinity, conductivity, and turbidity.

Advanced equipment includes: a FTIR system with MIR and DTGS detectors for the analyses of functional groups in solid or non-aqueous liquid samples, total organic halogen with ion chromatography system to measure the amount of TOX in liquid or solid samples, UV/Vis spectrophotometer for measuring absorbance or transmittance of liquid samples, florescence spectrometer for analyzing luminescence samples, programmable tube furnace with three control zones for various degree of combustion of different materials, and BET system for the characterization of surface area and pore volume of solid samples.

A relevant central facility is the Material Characterization and Preparation Facility comprising 10 main research groups: surface science, electron microscopy, scanning probe microscopy, x-ray diffraction, nuclear magnetic resonance, thin film deposition, optical characterization, electrical and magnetic characterization, thermal analysis, and sample preparation. Each research group houses state-of-the-art multidisciplinary instrumentation, supported by a team of experienced staff. Major items include X-ray diffraction systems, transmission electron microscopes, scanning electron microscopes, thin film sputtering and evaporation systems, a multi-technique surface analysis system (XPS Auger, ISS), a TOF-SIMS system, a Dynamic SIMS system, scanning probe microscopes (STM, AFM and MFM), FTIR/Raman spectrometers, thin film measurement systems, thermal analysis instruments.

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Working at the cutting edge of the field with top international scientists, our postgraduate programs seek to ensure that each student. Read more
Working at the cutting edge of the field with top international scientists, our postgraduate programs seek to ensure that each student:
-Attains an in-depth understanding of fundamental yet advanced chemical engineering topics
-Exercises intellectual curiosity in probing chemical engineering subjects at the frontiers of chemical engineering
-Develops skills to pursue new knowledge, both basic and applied, independently
-Engages in pioneering research in this and related disciplines

The Department emphasizes both academic excellence and industrial relevance and, wherever possible, programs are set in the context of local industrial needs and explore the potential of creating demand for new technologies. In addition to our own MPhil and PhD postgraduate degree programs, the Department also contributes to the degree programs in Biotechnology, and Materials Science and Engineering. Many research projects are interdisciplinary in nature and are carried out with other departments or institutions.

We have 18 full-time faculty members and 97 postgraduate students. Together with the best available equipment, the Department provides an ideal environment for tackling the challenges facing modern chemical engineers, generating significant developments and evolving new products.

The MPhil program aims to strengthen students’ fundamental knowledge of Chemical Engineering, with specialization in the areas of chemical processing, materials, environment, energy and bioengineering. Students will be exposed to relevant issues involved in the scientific research, technology development and commercial applications in the field. Those on the program are required to undertake coursework and successfully complete a thesis to demonstrate competence in research.

Research Foci

Chemical and Biomolecular Engineering is a highly diversified engineering and science discipline. The Department’s research can be classified into four major areas:

Advanced Materials
Nanomaterials, zoelites, novel polymers, polymer composites, polymer interfaces and surfaces as well as polymer/ceremic membranes. In-depth studies are being carried out in: rheology, non-Newtonian flow, heat and mass transport, and process control associated with the injection-molding process.

Bioprocess Engineering
Environmental biotechnology, Chinese traditional medicine (novel extraction, drying, packaging), biosensors (applications to wastewater treatment, genechips), food industries (batch processing), mathematical modeling/simulation, and process control. Research activities are supported by HKUST’s Biotechnology Research Institute.

Environmental Engineering
Air pollution formation and abatement, aerosols, deodorization of indoor air, catalytic and advanced oxidation, electrocoagulation and electrooxidation, advanced methods for wastewater treatment, hazardous wastes and micro-contamination, waste minimization and cleaner technologies.

Product and Process Design
Chemical processes, biochemical processes, environmental fate and transport, and surface phenomena and effects. The design of high value-added products, such as fuel cells, food additives, pharmaceuticals, is also an active research area.

Facilities

The Department has state-of-the-art analytical instrumentation, including a high-performance liquid chromatograph, gas chromatographs with a mass selective detector, flame ionization detector, inductively coupled plasma spectrometer, organic carbon analyzer, UV/visible spectrophotometer, differential scanning calorimeter, capillary rheometer and universal testing machine. In addition, each area of research has specific facilities available to it.

The University’s central facilities provide relevant supports, including an electronic support shop, instrumentation pool, machine shop and the Design and Manufacturing Services Facility. There are also advanced computing facilities, including a massive parallel processing computer.

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As the technical sophistication of most professions increases, there is growing need for individuals capable of “speaking the language” of mathematics. Read more
As the technical sophistication of most professions increases, there is growing need for individuals capable of “speaking the language” of mathematics. Mathematicians increasingly are sought to probe and expand mathematical theory, as engineering and empirical science delve deeper into nature. Individuals also are needed to teach the math skills that have expanded into virtually every field. MTSU’s Master of Science in Mathematics gets students involved in both the understanding and creation of advanced mathematics through quality instruction, opportunities for research, and close faculty-student interaction. A General Mathematics concentration is aimed at students desiring a broad background in mathematics. The Industrial Mathematics concentration is designed for students interested in positions in industry or further graduate work in applied mathematics. A Research Preparation concentration, which requires a thesis, is intended for students wishing to pursue the Ph.D. in Mathematics.

Students may choose from three concentrations for the Master of Science (M.S.) in Mathematics: General Mathematics, Industrial Mathematics, or Research Preparat

Career

A majority of M.S. in Mathematics graduates go on to pursue their doctoral degrees at a number of universities. Several students have also entered Ph.D. programs at MTSU in either the Computational Sciences or the Mathematics and Science Education Ph.D. programs.

General Mathematics concentration students usually work in fields which require the specialized thinking skills that mathematicians develop but which do not necessarily require a highly specialized mathematics background.

Research Preparation curriculum gives students a strong background in what is called pure mathematics for a career in academics and mathematical research.

Industrial Mathematics students focus on applied mathematics to work in fields which make heavy use of mathematical modeling. Mathematicians work with programmers to develop highly specialized software tools for engineering and medical applications. Mathematicians help develop or enhance sophisticated models for understanding weather, chemical, biological, or economic processes; and mathematicians create entirely new mathematical tools to probe frontiers in physics, structural design, and other pursuits.

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Choosing to take a Master of Science in Mathematics and Statistics at Acadia will deepen your mathematical knowledge, and develop your research and analytical skills. Read more
Choosing to take a Master of Science in Mathematics and Statistics at Acadia will deepen your mathematical knowledge, and develop your research and analytical skills. At the same time, you can earn your degree while gaining experience working and researching in industry.

Acadia's graduate program in mathematics and statistics offers you an exciting opportunity to earn your degree and tackle a significant research problem while also participating in our award-winning co-operative education option and gaining industry work experience. You will take courses that will broaden your knowledge and also prepare you to work on your chosen research project. Our co-operative education option allows you to gain eight months of industry experience work terms or internships. A special feature of the program is to be able to align your work experience and research project, allowing you to more deeply understand the importance and relevance of the research problem.

Be Inspired

In our program, you will benefit from the small school advantage – close contact with your supervisor and a program best-suited to your interests – while also being able to participate in a wide range of research that Acadia faculty conduct. In our department, you can pursue research into tidal energy in the Bay of Fundy, fractal images, games on graphs, statistical learning, big data, computer experiments, cryptography, number theory, scheduling theory, and statistical applications in agriculture, biology, and medicine.

Our department is associated with the Acadia Centre for Mathematical Modeling and Computation, ACENet and Compute Canada, which provide expertise and resources for applying computational resources towards solving problems in the mathematical sciences. The Statistical Consulting Centre creates opportunities to support local projects, and to consult on other research projects at the institution. Acadia's faculty engage in projects with local businesses, federal and provincial government agencies, the local tidal power and agricultural industries, and a variety of businesses nationally and internationally.

Research Interests

-Hugh Chipman: Tree models, variable selection, Bayesian methodology, data mining
-Nancy Clarke: Graph theory, combinatorics, design theory and game theory
-Eva Curry: Digital representations for vectors and connections to wavelet theory, iterated function systems, probability, and number theory
-Jeff Hooper: Algebraic number theory, cryptography
-Richard Karsten: Models of ocean circulation, climate modelling
-Wilson Lu: Survey sampling, replication methods, survey confidentiality, computer experiment design
-Franklin Mendivil: Image processing, stochastic optimization, fractal analysis
-Jianan Peng: Order restricted inference, multiple comparisons, nonparametric statistics
-Pritam Ranjan: Computer experiments, sequential designs, combinatorial designs
-Paul Stephenson: Machine scheduling, optimization algorithms
-Holger Teismann: PDE, control theory, non-linear optics
-Ying Zhang: Statistical computing, time series analysis, applied statistical modelling

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The MSc in Smart Grid Demand Management (See http://www.postgraduate.hw.ac.uk/prog/msc-smart-grid-demand-management/ ) has been designed to progress students with an Electrical or Mechanical Engineering background to an expert in the understanding of a smart grid. Read more

Overview

The MSc in Smart Grid Demand Management (See http://www.postgraduate.hw.ac.uk/prog/msc-smart-grid-demand-management/ ) has been designed to progress students with an Electrical or Mechanical Engineering background to an expert in the understanding of a smart grid. By following a carefully selected set of courses covering energy resources (fossil and renewable), conversion technologies, electrical power generation, energy storage technologies, demand management, and energy economics. Graduates of this programme will be confident in all aspects of this subject. With a clear focus on smart Grid and Demand Management the programme provides;
- Knowledge and understanding of advanced scientific and mathematical principles relevant to the understanding, analysis and modelling of a smart grid.
- An understanding of fundamental facts, concepts, and technologies for demand management and energy storage.
- Knowledge and skill to apply engineering principles to design a system, component or process
- An ability to undertake independent research.
- Professional attitudes to implementation of safety and concepts embodied by sustainability.
- An ability to communicate effectively
- Familiarity with the application of relevant computer tools to the profession.

All aspects of the smart grid are integrated in a dedicated smart grid modelling course, which provides the mathematical and computational skills to model a smart grid. This course is unique to this programme and will give graduates the skills they need to enhance their career prospects.

The Scottish Funding Council has made available 20 scholarships covering fees only to students with Scottish backgrounds. 5 of these places are reserved for applicants to this programme in the first instance. The remaining places are spread over all our Energy based MSc programmes. There is no separate application process for this. If you are eligible, you will be considered automatically. You will be notified through the summer if you have been selected.

Scholarships available

We have a number of fully funded Scottish Funding Council (SFC) scholarships available for students resident in Scotland applying for Smart Grid Demand Management MSc. Find out more about this scholarship and how to apply http://www.hw.ac.uk/student-life/scholarships/postgraduate-funded-places.htm .

Programme content

Semester One - All courses are Mandatory
- B51ET Foundations of Energy
This course provides the foundations for the quantitative analysis of energy resources and conversion efficiencies through various technologies. It also places energy production and consumption into the wider field of environmental and socio-economic factors

- B51GE Renewable Energy Technologies
This course introduces the range of Renewable Energy resources together with established and emerging technologies. It provides the skills for a quantitative assessment of the Renewable Energy resources and the expected energy and power output from typical or specific installations.

- B31GA Electrical Power Systems
This course covers the operation of interconnected electrical power systems. Such interconnected power systems combine a number of different components, generators, transmission lines, transformers and motors, which must be appreciated to understand the operation of the interconnected system.

- C21EN Environmental and Energy Economics
This course introduces students to the core concepts and methods of modern economics, and environmental and energy economics in particular.

Semester Two – All courses are Mandatory
- B31GG Smart grid modeling
This course introduces the mathematical skills to model the operation of an electricity or energy network at a statistical and dynamical level, incorporating key elements of a smart grid, including technological constraints, economic drivers and information exchange.

- B31GB Distributed Generation
This course equips students with an understanding of the role of distributed generation in electrical energy networks. It provides students with an overview of distributed generation techniques and describes the contribution of distributed generation to network security. The course introduces the economics of distributed generation and the assessment of distributed generation schemes. It introduces students to the concept of intermittent sources and their contribution to capacity in electrical power systems and provides a detailed review of the reliability, fault and stability studies of distributed generation schemes.

- B51GK Demand Management and Energy Storage
This course provides students with an overview of demand-side management and its contribution to network capacity and security. It reviews energy storage technologies and their contribution to the integration of renewable generation and the operation of large-scale electrical network. It introduces students to the methods of interfacing energy storage mechanisms to electrical networks. The course describes the contribution energy storage technology can make to transportation and industry

- B81EZ Critical Analysis and Research Preparation
This course provides research training and addresses literature review skills, project planning, data analysis and presentation with a focus to critically discuss literature, and use data to support an argument.

- B31VZ MSc Project
An individual project led by a research active member of staff or an industrial partner on a topic relevant to smart grid technology, demand management technologies or approaches or smart grid/ electricity / energy systems modelling.

English language requirements

If you are not from a UKBA recognised English speaking country, we will need to see evidence of your English language ability. If your first degree was taught in English a letter from them confirming this will be sufficient. Otherwise the minimum requirement for English language is IELTS 6.5 or equivalent, with a minimum of 5.5 in each skill.

The University offers a range English language courses (See http://www.hw.ac.uk/study/english.htm ) to help you meet the English language requirement prior to starting your masters programme:
- 14 weeks English (for IELTS of 5.5 with no more than one skill at 4.5);
- 10 weeks English (for IELTS of 5.5 with minimum of 5.0 in all skills);
- 6 weeks English (for IELTS 5.5 with minimum of 5.5 in reading & writing and minimum of 5.0 in speaking & listening)
- 3 weeks English refreshers course (for students who meet the English condition for the MSc but wish to refresh their English skills prior to starting).

Find information on Fees and Scholarships here http://www.postgraduate.hw.ac.uk/prog/msc-smart-grid-demand-management/

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The MSc Computational Finance will provide you with mathematical and computational skills required to solve real problems in quantitative finance. Read more
The MSc Computational Finance will provide you with mathematical and computational skills required to solve real problems in quantitative finance. Many areas of modern finance such as risk management and option pricing emphasise numerical and computational skills as well as an understanding of the mathematical background.

The programme brings together expertise from Mathematics and the Business School to ensure a balanced approach to many of the complex problems in modern quantitative finance.

On completion of the programme you will be able to review and implement complex financial models in a number of programming languages including C++, MATLAB and R.

Programme structure

Core modules

The compulsory modules can include; Methods for Stochastics and Finance; Analysis and Computation for Finance; Mathematical Theory of Optional Pricing; Introduction to C++; Computational Finance with C++; Numerical Finance; Research Methodology; Advanced Mathematics Project; Investment Analysis I; Investment Analysis II; Financial Modeling

Optional modules

Some examples of the optional modules are as follows; Topics in Financial Economics; Banking and Financial Services; Derivatives Pricing; Domestic and International Portfolio Management; Advanced Corporate Finance; Alternative Investments; Quantitative Research Techniques; Advanced Econometrics;

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The Department of Mathematics offers graduate courses leading to M.Sc., and eventually to Ph.D., degree in Mathematics. The Master of Science program aims to provide a sound foundation for the students who wish to pursue a research career in mathematics as well as other related areas. Read more
The Department of Mathematics offers graduate courses leading to M.Sc., and eventually to Ph.D., degree in Mathematics. The Master of Science program aims to provide a sound foundation for the students who wish to pursue a research career in mathematics as well as other related areas. The department emphasizes both pure and applied mathematics. Research in the department covers algebra, number theory, combinatorics, differential equations, functional analysis, abstract harmonic analysis, mathematical physics, stochastic analysis, biomathematics and topology.

Current faculty projects and research interests:

• Ring Theory and Module Theory, especially Krull dimension, torsion theories, and localization

• Algebraic Theory of Lattices, especially their dimensions (Krull, Goldie, Gabriel, etc.) with applications to Grothendieck categories and module categories equipped with torsion theories

• Field Theory, especially Galois Theory, Cogalois Theory, and Galois cohomology

• Algebraic Number Theory, especially rings of algebraic integers

• Iwasawa Theory of Galois representations and their deformations Euler and Kolyvagin systems, Equivariant Tamagawa Number
Conjecture

• Combinatorial design theory, in particular metamorphosis of designs, perfect hexagon triple systems

• Graph theory, in particular number of cycles in 2-factorizations of complete graphs

• Coding theory, especially relation of designs to codes

• Random graphs, in particular, random proximity catch graphs and digraphs

• Partial Differential Equations

• Nonlinear Problems of Mathematical Physics

• Dissipative Dynamical Systems

• Scattering of classical and quantum waves

• Wavelet analysis

• Molecular dynamics

• Banach algebras, especially the structure of the second Arens duals of Banach algebras

• Abstract Harmonic Analysis, especially the Fourier and Fourier-Stieltjes algebras associated to a locally compact group

• Geometry of Banach spaces, especially vector measures, spaces of vector valued continuous functions, fixed point theory, isomorphic properties of Banach spaces

• Differential geometric, topologic, and algebraic methods used in quantum mechanics

• Geometric phases and dynamical invariants

• Supersymmetry and its generalizations

• Pseudo-Hermitian quantum mechanics

• Quantum cosmology

• Numerical Linear Algebra

• Numerical Optimization

• Perturbation Theory of Eigenvalues

• Eigenvalue Optimization

• Mathematical finance

• Stochastic optimal control and dynamic programming

• Stochastic flows and random velocity fields

• Lyapunov exponents of flows

• Unicast and multicast data traffic in telecommunications

• Probabilistic Inference

• Inference on Random Graphs (with emphasis on modeling email and internet traffic and clustering analysis)

• Graph Theory (probabilistic investigation of graphs emerging from computational geometry)

• Statistics (analysis of spatial data and spatial point patterns with applications in epidemiology and ecology and statistical methods for medical data and image analysis)

• Classification and Pattern Recognition (with applications in mine field and face detection)

• Arithmetical Algebraic Geometry, Arakelov geometry, Mixed Tate motives

• p-adic methods in arithmetical algebraic geometry, Ramification theory of arithmetic varieties

• Topology of low-dimensional manifolds, in particular Lefschetz fibrations, symplectic and contact structures, Stein fillings

• Symplectic topology and geometry, Seiberg-Witten theory, Floer homology

• Foliation and Lamination Theory, Minimal Surfaces, and Hyperbolic Geometry

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Memorial’s Department of Mathematics and Statistics is one of the institution’s youngest – half our faculty have been hired since 2005 – and most recognized – 20% of us hold the university's highest rank, University Research Professor. Read more
Memorial’s Department of Mathematics and Statistics is one of the institution’s youngest – half our faculty have been hired since 2005 – and most recognized – 20% of us hold the university's highest rank, University Research Professor. Although the Department of Mathematics and Statistics has offered graduate degrees for many years, the past decade has seen an explosion of interest in these programs, adding invaluable new voices to the Department's community of researchers.

Among the research areas studied by our faculty and graduate students are the following: Numerical Analysis and Scientific Computation, Analysis, Combinatorics, Topology, Applied Statistics, Differential Equations and Dynamical Systems, Mathematical Models and Modeling / Numerical Optimization, Algebra, Mathematical Physics, Mathematical Statistics, and Fluid Mechanics.

MAS -The MAS is a highly structured program incorporating both courses and practicum (an applied statistics project). A full-time student with an honours degree in statistics normally requires two years to complete the degree requirements. This program accepts new students only in the Fall semester.

MSc – The MSc program has two options. The research-based program consists of graduate courses and a thesis. A full-time student is expected to complete the degree requirements in two years. The course-based program is an intensive three semester (one-year) program based on graduate courses and a project. This program accepts new students only in the Fall semester.

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This programme involves studying the interaction between and within groups of neurons in the brain, and how they affect our interactions with the outside world. Read more
This programme involves studying the interaction between and within groups of neurons in the brain, and how they affect our interactions with the outside world.

The brain is no longer considered a passive response device but rather as a network in which we consider ongoing activity before, during, and after a stimulus. The specialisation Brain Networks and Neuronal Communication deals with brain networks; ranging from the smallest scale, the communication between individual neurons, to the largest scale, communication between different brain areas. Using advanced mathematical tools, this specialisation prepares students for cutting-edge neuroscience research.
Students interested in this specialisation are expected to already have a high level of mathematical skills and/or training in physics, engineering or computer science in their Bachelor’s studies.

A large majority of our graduates gain a PhD position, while other graduates find jobs in the commercial sector or at research institutes. Graduates of this specialisation may more readily find a position within a government institution or specialised companies (e.g. in the pharmaceutical industry).

See the website http://www.ru.nl/masters/cns/brain

Why study Brain Networks and Neuronal Communication at Radboud University?

- Researchers in Nijmegen combine new techniques for electrophysiological and anatomical measurements of connectivity and activation with data analysis and the experimental application of these techniques. This is done in studies of cognition in not just humans but also non-human primates and rodents.
- Exceptional students who choose this specialisation have the opportunity to do a double degree programme with either Neuroscience or Artificial Intelligence. This will take three instead of two years.
- This competitive programme provides a sound balance of theory and practice. Our selective approach guarantees excellence, especially during the research training period.

Career prospects

If you have successfully completed the Master’s programme in Brain networks and neuronal communication, you will be able to conduct independent neuroimaging and neurobiological research. You will have ample knowledge of the anatomical and neurophysiological aspects of networks in the human brain and the techniques for the computational analysis and modeling of brain networks. This will enable you to conduct independent research into the neurofunctional architecture of key cognitive functions, such as perception, attention, memory, language, planning and targeted actions and develop technologies to measure, characterise and model networks at the whole brain and/or the local cortical circuit level. With this educational background you should be able to find a position with one of the research institutes in the Netherlands or abroad, government institutions or specialised companies (e.g. in the pharmaceutical industry).

Our approach to this field

Research in the field of cognitive neuroscience is one of the spearheads in the research policy of Radboud University. Here, in Nijmegen, hundreds of scientists from various faculties and top institutes have joined forces to unravel the workings of the human brain, step by step . They work together closely, exchange expertise and share state-of-the-art research equipment.

Nijmegen is one of the foremost centres of cognitive neuroscience in the world. We have a high admission threshold to ensure that all of our students are highly motivated and have the ability to work at an advanced level. Top scientists screen all applications to make sure the new students meet our stringent entry criteria and can maintain the current standards of excellence. Once admitted to the programme, you can expect to be trained as a multidisciplinary scientist in the following two years. The research you will undertake addresses crossdisciplinary challenges. The teachers and supervisors you will meet are all experts in their own disciplines. We hope that with this programme, you will outperform your teachers by being able to combine knowledge from different domains. Alongside language processing and perceptuomotor systems, you may also help improve brain/computer interfaces, a hot topic with applications in medicine and information technology. Apart from being very exciting, it is also logical that various disciplines are merging. After all, everything that happens in the brain is interconnected. In Nijmegen we develop sophisticated cognitive models which we test by means of state-of-the-art imaging techniques, thanks to which you can participate in cutting-edge research that will hopefully lead to new insights into the way the human brain and mind work. Finally, we offer our best CNS students excellent career opportunities in challenging PhD projects.

- Unique multi-disciplinary Master’s programme
Are you also interested in the human brain? Would you like to conduct research into the workings of the brain and join an enthusiastic, international group of top researchers? The Radboud University offers a multi-faculty Master’s programme in Cognitive Neuroscience. The programme takes two years and is of a scientific orientation. There is a strong emphasis on experimental research. This Master’s programme is unique in Europe.
The Master’s programme in Cognitive Neuroscience is primarily focused on training you as a researcher because research institutes and businesses around the world desperately need highly qualified and motivated young researchers. Moreover, since cognitive neuroscience is a rather young discipline, much in this field has not yet been explored. There are many challenging questions that need to be answered. So there is plenty of room for new discoveries!

This competitive programme provides a sound balance of theory and practice. We enrol about 50 students per year. Our selective approach guarantees excellence, especially during the research training period.

See the website http://www.ru.nl/masters/cns/brain

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