High-level training in statistics and the modelling of random processes for applications in science, business or health care.
For many complex systems in nature and society, stochastics can be used to efficiently describe the randomness present in all these systems, thereby giving the data greater explanatory and predictive power. Examples include statistical mechanics, financial markets, mobile phone networks, and operations research problems. The Master’s specialisation in Applied Stochastics will train you to become a mathematician that can help both scientists and businessmen make better decisions, conclusions and predictions. You’ll be able to bring clarity to the accumulating information overload they receive.
The members of the Applied Stochastics group have ample experience with the pure mathematical side of stochastics. This area provides powerful techniques in functional analysis, partial differential equations, geometry of metric spaces and number theory, for example. The group also often gives advice to both their academic colleagues, and organisations outside of academia. They will therefore not only be able to teach you the theoretical basis you need to solve real world stochastics problems, but also to help you develop the communications skills and professional expertise to cooperate with people from outside of mathematics.
See the website http://www.ru.nl/masters/mathematics/stochastics
- This specialisation focuses both on theoretical and applied topics. It’s your choice whether you want to specialise in pure theoretical research or perform an internship in a company setting.
- Mathematicians at Radboud University are expanding their knowledge of random graphs and networks, which can be applied in the ever-growing fields of distribution systems, mobile phone networks and social networks.
- In a unique and interesting collaboration with Radboudumc, stochastics students can help researchers at the hospital with very challenging statistical questions.
- Because the Netherlands is known for its expertise in the field of stochastics, it offers a great atmosphere to study this field. And with the existence of the Mastermath programme, you can follow the best mathematics courses in the country, regardless of the university that offers them.
- Teaching takes place in a stimulating, collegial setting with small groups. This ensures that you’ll get plenty of one-on-one time with your thesis supervisor at Radboud University .
- More than 85% of our graduates find a job or a gain a PhD position within a few months of graduating.
Mathematicians are needed in all industries, including the banking, technology and service industries, to name a few. A Master’s in Mathematics will show prospective employers that you have perseverance, patience and an eye for detail as well as a high level of analytical and problem-solving skills.
The skills learned during your Master’s will help you find jobs even in areas where your specialised mathematical knowledge may initially not seem very relevant. This makes your job opportunities very broad and is the reason why many graduates of a Master’s in Mathematics find work very quickly.
Possible careers for mathematicians include:
- Researcher (at research centres or within corporations)
- Teacher (at all levels from middle school to university)
- Risk model validator
- ICT developer / software developer
- Policy maker
Radboud University annually has a few PhD positions for graduates of a Master’s in Mathematics. A substantial part of our students attain PhD positions, not just at Radboud University, but at universities all over the world.
The research of members of the Applied Stochastics Department, focuses on combinatorics, (quantum) probability and mathematical statistics. Below, a small sample of the research our members pursue.
Eric Cator’s research has two main themes, probability and statistics.
1. In probability, he works on interacting particles systems, random polymers and last passage percolation. He has also recently begun working on epidemic models on finite graphs.
2. In statistics, he works on problems arising in mathematical statistics, for example in deconvolution problems, the CAR assumption and more recently on the local minimax property of least squares estimators.
Cator also works on more applied problems, usually in collaboration with people from outside statistics, for example on case reserving for insurance companies or airplane maintenance. He has a history of changing subjects: “I like to work on any problem that takes my fancy, so this description might be outdated very quickly!”
Hans Maassen researches quantum probability or non-commutative probability, which concerns a generalisation of probability theory that is broad enough to contain quantum mechanics. He takes part in the Geometry and Quantum Theory (GQT) research cluster of connected universities in the Netherlands. In collaboration with Burkhard Kümmerer he is also developing the theory of quantum Markov chains, their asymptotic completeness and ergodic theory, with applications to quantum optics. Their focal point is shifting towards quantum information and control theory, an area which is rapidly becoming relevant to experimental physicists.
Ross Kang conducts research in probabilistic and extremal combinatorics, with emphasis on graphs (which abstractly represent networks). He works in random graph theory (the study of stochastic models of networks) and often uses the probabilistic method. This involves applying probabilistic tools to shed light on extremes of large-scale behaviour in graphs and other combinatorial structures. He has focused a lot on graph colouring, an old and popular subject made famous by the Four Colour Theorem (erstwhile Conjecture).
See the website http://www.ru.nl/masters/mathematics/stochastics
Computing and communications technologies are having a truly disruptive effect on societies and business worldwide. Mobile payments, wireless communications and the ‘Internet of Things’ are transforming the way we approach key challenges in development, security, healthcare and the environment.
Taught jointly by the School of Computing and the School of Electronic and Electrical Engineering, this course will give you a grasp of all layers needed for mobile communication and computation, from the physical network layer through to the applications that run on mobile devices.
You’ll gain a full understanding of the web and cloud computing infrastructure, as core modules give you a foundation in key topics like systems programming and data communications. A range of optional modules will then allow you to focus on topics that suit your interests and career plans, from cloud computing to embedded systems design and high speed web architecture.
You’ll benefit from world-class facilities to support your learning. State-of-the-art visualisation labs including a powerwall, a benchtop display with tracking system, WorldViz PPT optical tracking system and Intersense InertiaCube orientation tracker are all among the specialist facilities we have within the School of Computing.
We also have Ascension Flock of Birds tracking systems, three DOF and 6DOF Phantom force feedback devices, Twin Immersion Corp CyberGloves, a cloud computing testbed, rendering cluster and labs containing both Microsoft and Linux platforms among others. It’s an exciting environment in which to gain a range of skills and experience cutting-edge technology.
You’ll take two core modules in Semester 1 that introduce you to fundamental topics like systems programming and network security. With this foundation, you’ll be able to gain high-level specialist knowledge through your choice of optional modules taught by the School of Computing and the School of Electronic and Electrical Engineering.
The optional modules you choose will enable you to direct your studies towards topics that suit your personal interests and career ambitions such as mobile app development, digital media engineering, big data, cloud computing and embedded systems design, among others.
Over the summer months you’ll also work on your research project. This gives you the chance to work as an integral part of one of our active research groups, focusing on a specialist topic in computer science and selecting the appropriate research methods.
Our groundbreaking research feeds directly into teaching, and you’ll have regular contact with staff who are at the forefront of their disciplines. You’ll have regular contact with them through lectures, seminars, tutorials, small group work and project meetings.
Independent study is also important to the programme, as you develop your problem-solving and research skills as well as your subject knowledge.
You’ll be assessed using a range of techniques including case studies, technical reports, presentations, in-class tests, assignments and exams. Optional modules may also use alternative assessment methods.
The professional project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests.Most projects are experimentally based and linked with companies within the oil and gas industry to ensure the topic of research is relevant to the field whilst also addressing a real-world problem.
A proportion of projects are formally linked to industry, and can include spending time at the collaborator’s site over the summer.
Career opportunities are extremely broad, covering jobs in the design of embedded software running on multi-core devices through to jobs involving the design and implementation of new mobile-applications centric systems for business. In the application of mobile computing skills, job opportunities span every area, from the automotive sector through to retail and banking.
You could launch a career in fields such as mobile app development, mobile systems architecture, project management, network consultancy. You could also work as an engineer in embedded mobile communications, network security or research and development among many others – and you’ll even be well-prepared for PhD study.
You’ll have access to the wide range of engineering and computing careers resources held by our Employability team in our dedicated Employability Suite. You’ll have the chance to attend industry presentations book appointments with qualified careers consultants and take part in employability workshops. Our annual Engineering and Computing Careers Fairs provide further opportunities to explore your career options with some of the UK’s leading employers.
The University's Careers Centre also provide a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.
In this MRes Mathematical Sciences course, you will gain deep knowledge of a chosen topic in mathematics or statistics and develop your research skills in project planning, reviewing literature, group discussions, research presentations and writing publications.
You can choose to work with experts from a range of areas including quantum cryptography, graph theory, statistical analysis, bioinformatics and mathematical modelling.
You will take three taught modules each providing you with the underpinning theory to support your research work.
Visit us on campus throughout the year, find and register for our next open event on http://www.ntu.ac.uk/pgevents.
The Department of Mathematics at The University of Tennessee at Chattanooga offers a Master of Science degree in mathematics with concentrations in applied mathematics, applied statistics, pre-professional mathematics, and education. This program is designed to provide individuals with an in-depth understanding in their chosen area, further preparing them for work in industry, government, and education, or for further graduate studies. Completion of the program requires thirty-six (36) semester credit hours, which includes an area of application or an internship. There is also an option of composing a final thesis. Students must maintain a minimum institutional cumulative GPA of 3.0, and are subject to all regulations of the UTC Graduate School.
The Department of Mathematics has 21 full time faculty members holding professorial rank, all of whom hold the Ph.D. degree. The graduate faculty has 21 members and their research interests span a wide variety of mathematical interests. These include linear algebra and matrix theory, modern algebra, graph theory, numerical analysis, functional analysis, ordinary and partial differential equations and difference equations, operations research, statistics and mathematics education. The Department is highly active in research as demonstrated by publications in national and international refereed journals, invited and contributed presentations at national and international conferences, service on editorial boards, and refereeing and reviewing activities. In 2005-06, more than twenty papers appeared in print, several more were accepted for publication, and more than 25 papers were presented at national and international conferences. In 2013, more than 54 papers appeared in print, several more were accepted for publication, and more than 25 papers were presented at national and international conferences.
The department currently has 86 declared majors, an active Pi Mu Epilson fraternity, and a weekly colloquium series. The MS Program has been in existence since Fall 2009, and there are 12 full time graduate students employed as teaching assistants along with a number of students taking graduate level math courses on a part time basis. With an endowment of over $1 million, the Department is able to offer very competitive assistantships and fellowships for graduate study.
A minimum of thirty six (36) semester hours is required. At least twenty four (24) must be in mathematics at the 5000 level.
Zero (0) to nine (9) hours depending on whether these courses were taken at the undergraduate level:
Area of Application or Internship
Students may complete a minimum of six (6) credit hours in an area of application or an internship. The student and his or her graduate program committee will jointly decide upon the area of application or internship, and must be approved by the Graduate Coordinating Committee. It should be consonant with the chosen concentration. An oral presentation and a written report on the internship or area of application are required. Typically, students choosing an area of application will complete coursework in another department or college such as Business, Economics, Computer Science, Engineering, Physics, Chemistry, or Biology. In keeping with the interdisciplinary nature of this program, if a student chooses an area of application, the Graduate Coordinating Committee will ask that a representative from the outside area be added as an additional member of the student’s graduate program committee. Students choosing the internship option will usually collaborate with a local business. Options include businesses in the health insurance field, industrial and manufacturing industries, engineering firms, etc.
As needed to complete thirty six (36) hours. This may include zero (0) to three (3) hours for a special project, or as many as six (6) hours for a thesis.
If you want to study for a mathematics-related MSc course but don’t meet the full academic entry requirements, this programme will equip you with the mathematical knowledge and skills you need.
You’ll choose from a range of undergraduate modules offered in the School of Mathematics, building a programme which fills the gaps in your knowledge and prepares you for postgraduate study in your chosen field. If you complete the GradDip and meet the required performance standard, you’ll be eligible to apply for a number of related MSc courses in the next academic year.
You could develop your understanding of graph theory or quantum mechanics, algebra or calculus, financial statistics or coding theory among many others in a supportive and stimulating research environment.