This new and innovative course builds upon the integrated nature of the School of Dentistry’s clinical and basic science divisions, and aims to prepare future researchers, from scientific or clinical backgrounds for research careers based in addressing oral health needs. You’ll gain a thorough background in oral sciences, the investigative, cutting edge technologies that enable oral scientific discovery and the necessary training in research governance and rigour. All areas of translational research pathways will be addressed, including aspects of commercialisation which will be taught through the Leeds University Business School (LUBS). Disease focused modules provide opportunities for in-depth exploration with research experts in the fields of Cancer, Musculoskeletal and Oral and systemic disease links.
Our teaching staff includes world leading experts with track records in translating research discoveries into novel healthcare products and practices. Student integration within the wider Dental school will be facilitated by undertaking recently updated modules shared with students from other MSc programmes.
Aimed at dental and biosciences graduates, the course will facilitate a career path focussed on oral research and its translation into positive impacts on health.
The programme will:
Teaching will be split between the Dental school on the main campus and the Wellcome Trust Brenner Building (WTBB) at the St James’s University Hospital. The WTBB is a modern purpose built research facility, housing cutting edge facilities in imaging, tissue and microbiological culture and next generation sequencing technologies. On the main campus students can benefit from all the expertise, facilities (such as the Leeds Dental Translational and Clinical Research Unit) and support provided by the Dental school.
Our course emphasises student directed and multidisciplinary learning. Teaching methods include lectures, seminars and workshops, complemented by e-learning and will be delivered by research active scientists and clinicians with additional input from industrial partners and Leeds University Business School (LUBS) academics.
Summative assessment will provide you with on-going feedback on your depth of subject knowledge and skills. Assessment methods for formative and summative assessment will include oral and poster presentations, unseen examinations and literature reviews. Exercises to identify research questions formulate research plans and prepare mock applications for funding and ethical/ governance approvals will also contribute to assessment.
You will gain insight into all stages of translational research, preparing you for a career working across multi-disciplinary teams within research and innovation management. The course aims to enhance your career prospects of securing PhD studentship positions, whether that be in pre-clinical or clinical research.
The innovation management in practice module enables you to learn about the commercial aspects of translational research. It may be that you want to go into the oral healthcare industry, so knowledge of business skills will be a useful transferable skill.
You may want to go into academic teaching positions within your own country; this MSc will provide the knowledge required to teach oral biology at undergraduate level.
Research training opportunity based on a single project in molecular, environmental or medical microbiology.
Note: Financial support/funding for your training may be available - please see below.
For further details please go to http://www.kingston.ac.uk/research/research-degrees/fees/
The project can start at any time. Training duration (full time) - 1 year.
The candidates will be able to select a title from the list below, or suggest their own project relevant to research conducted in the host laboratory. Our priority areas of studies are: molectual mechanisms of interaction between pathogenic bacteria and host cells, virulence factors, mechanisms of bacterial stress response, molecular genetics and genomics with a focus on Campylobacter jejuni and other bacterial pathogens.
(1) Investigation of host-pathogen interaction (e.g. to study of adhesins of Campylobacter jejuni and cognate host cell receptors)
(2) Application of IonTorrent Next Generation Sequencing for comparative analysis of bacterial pathogens (e.g. to study genetic mechanisms responsible for structural variation of a capsular polysaccharide of Campylobacter jejuni)
The research will employ a wide range of state of the art microbiological and molecular biology techniques, and a successful candidate will receive extensive training and support from an experienced supervisor.
It is expected that the student will actively participate in scientific meetings and writing research articles with a possibility to progress to a PhD, and a postdoctoral post in future (depending on performance).
- enthusiastic and eager to learn;
- keen on research in molecular microbiology in general, and in investigation of bacterial pathogens in particular.
- some basic skills in bench work would be beneficial.
Please fill-in the application form available at
Email this along with evidence of educational qualification and any other supporting documents (e.g. University Certificates and exam transcripts, English Language test Certificate if applicatble, etc) to Prof. A. Karlyshev - [email protected]
Please also ask two referees who are familiar with your academic ability (or any relevant work experience) to email references to Prof. A. Karlyshev - [email protected]
You may be eligible to apply for a studentship/bursary to support your training, and may find useful the following links and contact details:
Funding opportunities listed at Faculty of Science, Engineering and Computing
General info and links
Loyalty bursaries for alumni and families
Annual Fund scholarships
Postgraduate Admissions Office
Faculty of Science, Engineering and Computing
Accessible via Switchboard tel. +44 (0)20 8417 9000
Tel: +44(0)20 8417 3221
Email: [email protected]
Tel: +44 (0)20 8417 3112
Email: [email protected]
Tel: +44 (0)20 8417 3112
Email: [email protected]
Note: any further enquiries regarding these training opportunities (not related to funding) should be addressed to Prof. A. Karlyshev [email protected]
Visit the MSc by Research in Molecular Microbiology page on the Kingston University website for more details!
Please see course description
£3996 (home students) or £13,000 (overseas students), plus bench fees, £3,000.
The course will enable biomedical & clinical students (including research midwives and nurses) to develop an academic and contemporary understanding of the biological and environmental influences that impact on pregnancy and the lifelong physical and mental wellbeing health of women and their infants
Students will gain insight and knowledge of how translation of basic science and clinical observation can lead to cutting edge research studies into new diagnostic and treatments both in the UK and in low resource settings globally. .
Students will develop scientific and clinical practical research skills, including statistics, so that they can confidently critically evaluate others research design and results, and apply these to their own research. They will also be given the necessary research knowledge and skills to design, plan, navigate research governance pathways, and conduct and analyse their own research project. Both scientific and clinical research projects are offered.
The MSc Women and Children's Health comprises three core taught modules, including ‘Fundamentals of Womens and Children’s Health’ which covers health and disease from the periconception period to birth and early childhood. Research led lectures will cover topics such as infertility, pre-pregnancy health, placentation, preeclampsia; immunology of pregnancy and autoimmune disease, metabolic disease in pregnancy, parturition and dysfunctional labour, miscarriage and preterm birth, lactation and infant nutrition, the developing brain and prematurity, childhood diet and dental health, premature infant and the neonatal lung, gut microbiome, obesity, childhood allergy, epigenetics and lifelong health, nutrition and global health and perinatal mental health.
The other required taught modules are Statistics and Research Governance, and Scientific and Clinical Research skills followed by an intensive six month core research projectwithin a lab or clinical research group.
Students can also select 1-2 optional taught module(s) to tailor the course to their developing interests, examples include Perinatal Mental Health, Ethics in Child Health, Regenerative Medicine, Principles of Implementation and Improvement, Science, Leadership and Management, Birth Defects, Assisted Conception, Regenerative Medicine and Global Women's Health.
The programme fosters intellectual skills of students through:
A typical week would be have approximately 10-15 hours teaching with the remaining hours dedicated to self-guided learning. In the final semester, research projects are full time with hours dedicated to practical and data collection, data analysis and writing.
You will study via a combination of lectures, journal clubs, group discussions, practicals, workshops and independent study.
Peer feedback, in course assignments such as data handling, research project and project report write-up, journal club, presentations and essays. All will be actively encouraged throughout the research project.
Typically, one credit equates to 10 hours of work.
We will assess you through a combination of coursework, seen/unseen written exams, essays, problem directed learning exercises, case studies, ethical problem debate, data-handling, creation of clinical study materials such as patient information sheets and consent forms, research proposal, oral presentations, and a final research project report.
The study time and assessment methods detailed above are typical and give you a good indication of what to expect. However, they may change if the course modules change.
The course will prepare scientists and clinicians for further research into Womens & Children’s Health
Research in the Division of Genetics and Genomics aims to advance understanding of complex animal systems and the development of improved predictive models through the application of numerical and computational approaches in the analysis, interpretation, modelling and prediction of complex animal systems from the level of the DNA and other molecules, through cellular and gene networks, tissues and organs to whole organisms and interacting populations of organisms.
The biology and traits of interest include: growth and development, body composition, feed efficiency, reproductive performance, responses to infectious disease and inherited diseases.
Research encompasses basic research in bioscience and mathematical biology and strategic research to address grand challenges, e.g. food security.
Research is focussed on, but not restricted to, target species of agricultural importance including cattle, pigs, poultry, sheep; farmed fish such as salmon; and companion animals. The availability of genome sequences and the associated genomics toolkits enable genetics research in these species.
Expertise includes genetics (molecular, quantitative), physiology (neuroendocrinology, immunology), ‘omics (genomics, functional genomics) with particular strengths in mathematical biology (quantitative genetics, epidemiology, bioinformatics, modelling).
The Division has 18 Group Leaders and 4 career track fellows who supervise over 30 postgraduate students.
Studentships are of 3 or 4 years duration and students will be expected to complete a novel piece of research which will advance our understanding of the field. To help them in this goal, students will be assigned a principal and assistant supervisor, both of whom will be active scientists at the Institute. Student progress is monitored in accordance with School Postgraduate (PG) regulations by a PhD thesis committee (which includes an independent external assessor and chair). There is also dedicated secretarial support to assist these committees and the students with regard to University and Institute matters.
All student matters are overseen by the Schools PG studies committee. The Roslin Institute also has a local PG committee and will provide advice and support to students when requested. An active staff:student liaison committee and a social committee, which is headed by our postgraduate liaison officer, provide additional support.
Students are expected to attend a number of generic training courses offered by the Transkills Programme of the University and to participate in regular seminars and laboratory progress meetings. All students will also be expected to present their data at national and international meetings throughout their period of study.
In 2011 The Roslin Institute moved to a new state-of-the-art building on the University of Edinburgh's veterinary campus at Easter Bush. Our facilities include: rodent, bird and livestock animal units and associated lab areas; comprehensive bioinformatic and genomic capability; a range of bioimaging facilities; extensive molecular biology and cell biology labs; café and auditorium where we regularly host workshops and invited speakers.
The University's genomics facility Edinburgh Genomics is closely associated with the Division of Genetics and Genomics and provides access to the latest genomics technologies, including next-generation sequencing, SNP genotyping and microarray platforms (genomics.ed.ac.uk).
In addition to the Edinburgh Compute and Data Facility’s high performance computing resources, The Roslin Institute has two compute farms, including one with 256 GB of RAM, which enable the analysis of complex ‘omics data sets.
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.