We offer an opportunity to train in one of the newest areas of biology: the application of engineering principles to the understanding and design of biological networks. This new approach promises solutions to some of today’s most pressing challenges in environmental protection, human health and energy production.
This MSc will provide you with a thorough knowledge of the primary design principles and biotechnology tools being developed in systems and synthetic biology, ranging from understanding genome-wide data to designing and synthesising BioBricks.
You will learn quantitative methods of modelling and data analysis to inform and design new hypotheses based on experimental data. The University’s new centre, SynthSys, is a hub for world-leading research in both systems and synthetic biology.
The programme consists of two semesters of taught courses followed by a research project and dissertation, which can be either modelling-based or laboratory-based.
The programme is designed to give you a good basis for managerial or technical roles in the pharmaceutical and biotech industries. It will also prepare you for entry into a PhD programme.
Life Sciences is one of the strategic research fields at the University of Helsinki. The multidisciplinary Master’s Programme in Life Science Informatics (LSI) integrates research excellence and research infrastructures in the Helsinki Institute of Life Sciences (HiLIFE).
The Master's Programme is offered by the Faculty of Science. Teaching is offered in co-operation with the Faculty of Medicine and the Faculty of Biological and Environmental Sciences. As a student, you will gain access to active research communities on three campuses: Kumpula, Viikki, and Meilahti. The unique combination of study opportunities tailored from the offering of the three campuses provides an attractive educational profile. The LSI programme is designed for students with a background in mathematics, computer science and statistics, as well as for students with these disciplines as a minor in their bachelor’s degree, with their major being, for example, ecology, evolutionary biology or genetics. As a graduate of the LSI programme you will:
Further information about the studies on the Master's programme website.
The Life Science Informatics Master’s Programme has six specialisation areas, each anchored in its own research group or groups.
Algorithmic bioinformatics with the Genome-scale algorithmics, Combinatorial Pattern Matching, and Practical Algorithms and Data Structures on Strings research groups. This specialisation area educates you to be an algorithm expert who can turn biological questions into appropriate challenges for computational data analysis. In addition to the tailored algorithm studies for analysing molecular biology measurement data, the curriculum includes general algorithm and machine learning studies offered by the Master's Programmes in Computer Science and Data Science.
Applied bioinformatics, jointly with The Institute of Biotechnology and genetics.Bioinformatics has become an integral part of biological research, where innovative computational approaches are often required to achieve high-impact findings in an increasingly data-dense environment. Studies in applied bioinformatics prepare you for a post as a bioinformatics expert in a genomics research lab, working with processing, analysing and interpreting Next-Generation Sequencing (NGS) data, and working with integrated analysis of genomic and other biological data, and population genetics.
Biomathematics with the Biomathematics research group, focusing on mathematical modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of topics ranging from problems at the molecular level to the structure of populations. To tackle these problems, the research group uses a variety of modelling approaches, most importantly ordinary and partial differential equations, integral equations and stochastic processes. A successful analysis of the models requires the study of pure research in, for instance, the theory of infinite dimensional dynamical systems; such research is also carried out by the group.
Biostatistics and bioinformatics is offered jointly by the statistics curriculum, the Master´s Programme in Mathematics and Statistics and the research groups Statistical and Translational Genetics, Computational Genomics and Computational Systems Medicine in FIMM. Topics and themes include statistical, especially Bayesian methodologies for the life sciences, with research focusing on modelling and analysis of biological phenomena and processes. The research covers a wide spectrum of collaborative topics in various biomedical disciplines. In particular, research and teaching address questions of population genetics, phylogenetic inference, genome-wide association studies and epidemiology of complex diseases.
Eco-evolutionary Informatics with ecology and evolutionary biology, in which several researchers and teachers have a background in mathematics, statistics and computer science. Ecology studies the distribution and abundance of species, and their interactions with other species and the environment. Evolutionary biology studies processes supporting biodiversity on different levels from genes to populations and ecosystems. These sciences have a key role in responding to global environmental challenges. Mathematical and statistical modelling, computer science and bioinformatics have an important role in research and teaching.
Systems biology and medicine with the Genome-scale Biology Research Program in Biomedicum. The focus is to understand and find effective means to overcome drug resistance in cancers. The approach is to use systems biology, i.e., integration of large and complex molecular and clinical data (big data) from cancer patients with computational methods and wet lab experiments, to identify efficient patient-specific therapeutic targets. Particular interest is focused on developing and applying machine learning based methods that enable integration of various types of molecular data (DNA, RNA, proteomics, etc.) to clinical information.
The Bioinformatics MSc combines foundational skills in bioinformatics with specialist skills in computing programming, molecular biology and research methods. Our unique, interdisciplinary course draws together highly-rated teaching and research expertise from across the University, equipping you for a successful career in the bioinformatics industry or academia.
This interdisciplinary course is based in the School of Computing Science and taught jointly with the School of Biology, School of Mathematics and Statistics, Institute of Cell and Molecular Biosciences and the Institute of Genetic Medicine. It is designed for students from both biological science and computational backgrounds. Prior experience with computer programming is not required and we welcome applications from students with mathematical, engineering or other scientific backgrounds.
Our graduates have an excellent record of finding employment (around 90%). Recent examples have included:
-Bioinformatician at the Medical Research Council
-Technical consultant at Accenture
-Bioinformatics technician at Barcelona Supercomputing Centre.
Our course structure is highly flexible and you can tailor it to your own skills and interests. Half of the course is taught and the remainder is dedicated to a research project.
As research is a large component of this course, our emphasis is on delivering the research training you will need to meet the demands of industry and academia now and in the future. Our research in bioinformatics, life sciences, computing and mathematics is internationally recognised. We have an active research community, comprising several research groups and three research centres.
You will be taught by academics who are successful researchers in their field and publish regularly in highly-ranked bioinformatics journals. Our experienced and helpful staff will be happy to offer support with all aspects of your course from admissions to graduation and developing your career.
The course is part of a suite of related programmes that include:
-Synthetic Biology MSc
-Computational Neuroscience and Neuroinformatics MSc
-Computational Systems Biology MSc
All four courses share core modules. This creates a tight-knit cohort that has encouraged collaborations on projects undertaking interdisciplinary research.
Semester one combines bioinformatics theory and application with the computational and modelling skills necessary to undertake more specialist modules in semester two. We provide training in mathematics and statistics and, for those without a biological first degree, we will also provide molecular biology training. Some of these modules are examined in January at the end of semester one.
Semester two begins with two modules that focus heavily on introducing subject-specific research skills. These two modules run sequentially, in a short but intensive mode that allows you time to focus on a single topic in depth. In the first of the second semester modules you learn how to analyse data arising from post-genomic studies such as microarray analysis, proteomic analysis and RNAseq. All of the semester two modules are examined by in-course assessment - there are no formal examinations in these modules.
Your five month project gives you an opportunity to develop your knowledge and skills in depth, and to work in a research or development team. You will have one-to-one supervision from an experienced member of staff, supported with supervision from industry partners as required.
The project can be carried out:
-With a research group at Newcastle University
-With an industrial sponsor
-With a research institute
-At your place of work.
We have a policy of seeking British Computer Society (BCS) accreditation for all of our degrees, so you can be assured that you will graduate with a degree that meets the standards set out by the IT industry. Studying a BCS-accredited degree provides the foundation for professional membership of the BCS on graduation and is the first step to becoming a chartered IT professional.
The School of Computing Science at Newcastle University is an accredited and a recognised Partner in the Network of Teaching Excellence in Computer Science.
The Modelling Biological Complexity MRes is designed for students who wish to develop the skills to apply mathematical, computational and physical science techniques to real biological problems. The programme provides a broad overview of the cutting edge research at the interface of the life, mathematical and physical sciences.
Foundation courses use innovative teaching methods for interdisciplinary research to provide essential background knowledge in mathematical, computational and physical techniques and a broad introduction to core biological concepts and systems. A range of interdisciplinary research-driven projects follow in which students gain experience of different research techniques and a range of areas of biological interest.
Students undertake modules to the value of 180 credits.
The programme consists of four compulsory modules: foundation courses module, transferable skills module (20%), three mini projects (40%) and a research (summer) project (40%).
There are no optional modules for this programme.
All students undertake an independent research (summer) project, which culminates in a dissertation of up to 15,000 words, a short presentation and an oral examination.
Teaching and learning
The programme is delivered through a combination of lectures, laboratory work, case presentations, seminars, tutorials and project work. Student performance is assessed by essays, mini projects, oral and poster presentations, a computer programming and biological database task, web development, the research project and an end-of-year viva.
Further information on modules and degree structure is available on the department website: Modelling Biological Complexity MRes
After passing the MRes, students may have the opportunity to progress onto a PhD at UCL.
CoMPLEX has built upon relationships with partners within academia and industry, to develop our existing CoMPLEX programme. so that it continues to be designed specifically to provide training that meets market needs. Graduates have excellent publication outputs, this, together with CoMPLEX's international reputation means that graduates are and will continue to be recognised when entering the job market. 70% of recent graduates have taken up positions in research centres in the UK and abroad. As small number have pursued careers in science policy analysis, cyber security, science teaching, statistical and mathematical consultancy, technology consultancy, or in management and the financial sector.
CoMPLEX is UCL's centre for interdisciplinary research in the life sciences. It brings together life and medical scientists with computer scientists, mathematicians, physicists and engineers to tackle the challenges arising from complexity in biology and medicine.
CoMPLEX collaborates with 250+ supervisors from 40 UCL Departments and maintains strong links with leading UK/International research institutions, charities and industrial partners e.g. AstraZeneca, British Heart Foundation, CRUK, Francis Crick Institute, GlaxoSmithKline, Microsoft Research and Renishaw. As a result CoMPLEX students have a vast range of projects to choose from and the opportunity to network with a plethora of scientific partners.
Peer-to-peer learning is a crucial part of the training, and students will take part in cohort activities, such as, mentoring events, a seminar series, outreach groups and an annual retreat.
The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.
Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.
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.
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
- 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.
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.
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.
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.
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. In addition, Jacobs University offers accommodation for graduate students on or off campus.
Bioinformaticians are distinguished by their ability to formulate biologically relevant questions, design and implement the appropriate solution by managing and analysing high-throughput molecular biological and sequence data, and interpret the obtained results.
This interdisciplinary two-year programme focuses on acquiring
The 120-credit programme consists of a reorientation package (one semester), a common package (two semesters) and a thesis.
The Master of Bioinformatics is embedded in a strong bioinformatics research community in KU Leuven, who monthly meet at the Bioinformatics Interest Group. Bioinformatics research groups are spread over the Arenberg and Gasthuisberg campus and are located in the research departments of Microbial and Molecular Systems (M2S), Electrical Engineering (ESAT), Human Genetics, Microbiology and Immunology (REGA), Cellular and Molecular Medicine, Chemistry and Biology. Several of these bioinformatics research groups are also associated with the Flemish Institute for Biotechnology (VIB).
Are you a biochemist or molecular biologist with a keen interest in mathematics and programming? Are you a mathematician or statistician and want to apply your knowledge to complex biological questions? Do you want to develop new methods that can be used by doctors, biologists and biotechnology engineers? Then this is the right program for you!
Bioinformaticians find careers in the life sciences domain in the broadest sense: industry, the academic world, health care, etc. The expanding need for bioinformatics in biological and medical research ensures a large variety of job opportunities in fundamental and applied research. 60% of our graduates start a PhD after graduation.