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Masters Degrees (Phylogenetic)

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visit course pages for more information about the next Open Day at NHM on Wednesday 7 June 2017. Taxonomy and systematics provide the foundation for studying the great diversity of the living world. Read more

Open Day

visit course pages for more information about the next Open Day at NHM on Wednesday 7 June 2017.

Course Overview

Taxonomy and systematics provide the foundation for studying the great diversity of the living world. These fields are rapidly changing through new digital and molecular technologies. There is ever greater urgency for species identification and monitoring in virtually all the environmental sciences, and evolutionary ‘tree thinking’ is now applied widely in most areas of the life sciences.

This course provides in-depth training in the study of biodiversity based on the principles of phylogenetics, evolutionary biology, palaeobiology and taxonomy. The emphasis is on quantitative approaches and current methods in DNA-based phylogenetics, bioinformatics, and the use of digital collections.

Location

This course is a collaboration of Imperial College London (Silwood Park) with the Natural History Museum. This provides an exciting scientific environment of two institutions at the forefront of taxonomic and evolutionary research.

The MSc in Taxonomy and Biodiversity comprises two terms of taught modules, mostly based at the Natural History Museum, and covers core areas in biodiversity, palaeobiology, phylogenetics, molecular systematics, phylogenomics and taxonomic principles. This is followed by a 16-week laboratory or field-based research project at the NHM or Imperial College’s Silwood Park or South Kensington campuses.

Modules

• Taxonomy of major groups and the Tree-of-Life: An introduction of major branches of the Tree, including identification exercises, presented by NHM experts
• Statistics and Computing: A two-week intensive course at Silwood Park
• Field course: trapping and collecting techniques for terrestrial and aquatic ecosystems
• Phylogenetic Reconstruction: the principles of building phylogenetic trees
• Molecular Systematics: generating and analysing molecular data; model-based phylogenetics
• Phylogenomics: Genomic techniques for studying evolutionary processes and biodiversity
• Biodiversity (Concepts): speciation, radiation, macroevolution
•Biodiversity (Applied): Measuring biodiversity, geospatial analysis, collection management and biodiversity informatics
• Palaeobiology: Studying the fossil record and what we can learn for biodiversity

Post Study

Students on the course will become the new generation of taxonomists in the broadest sense. They will be familiar with these new tools, as well as the wider concepts of biodiversity science, evolutionary biology and genomics. Most importantly, students gain the abilities to work as an independent scientist and researcher, to be able to solve questions about the future of biodiversity and to communicate them to peers and the public.
Students have many options for future employment in evolutionary and ecological research labs in industry, government and non-governmental organisations, conservation, and scientific publishing and the media. The courses are an excellent starting point for PhD level careers, feeding into various Doctoral Training Programmes available at NHM and Imperial, or elsewhere.

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With whole genome sequences being available for numerous organisms across all kingdoms of life, numerous questions concerning genome evolution to gene function, phylogenetic relationships to genetic and metabolic networks, genotype to phenotype of complex traits, can be addressed through comparative genomics. Read more
With whole genome sequences being available for numerous organisms across all kingdoms of life, numerous questions concerning genome evolution to gene function, phylogenetic relationships to genetic and metabolic networks, genotype to phenotype of complex traits, can be addressed through comparative genomics. Bioinformatic analysis of related genomes leads to testable hypotheses. Research available covers all of these areas and will use our expertise and resources on genome sequences to yeasts and fungi.

APPLICATION PROCEDURES

After identifying which Masters you wish to pursue please complete an on-line application form
https://pgapps.nottingham.ac.uk/
Mark clearly on this form your choice of course title, give a brief outline of your proposed research and follow the automated prompts to provide documentation. Once the School has your application and accompanying documents (eg referees reports, transcripts/certificates) your application will be matched to an appropriate academic supervisor and considered for an offer of admission.

COURSE STRUCTURE
The MRes degree course consists of two elements:
160 credits of assessed work. The assessed work will normally be based entirely on a research project and will be the equivalent of around 10 ½ months full-time research work. AND
20 credits of non-assessed generic training. Credits can be accumulated from any of the courses offered by the Graduate School. http://www.nottingham.ac.uk/gradschool/research-training/index.phtml The generic courses should be chosen by the student in consultation with the supervisor(s).

ASSESSMENT
The research project will normally be assessed by a dissertation of a maximum of 30,000 to 35,000 words, or equivalent as appropriate*. The examiners may if they so wish require the student to attend a viva.
*In consultation with the supervisor it maybe possible for students to elect to do a shorter research project and take a maximum of 40 credits of assessed modules.

The School of Life Sciences will provide each postgraduate research student with a laptop for their exclusive use for the duration of their studies in the School.

SCHOLARSHIPS FOR INTERNATIONAL STUDENTS

http://www.nottingham.ac.uk/studywithus/international-applicants/scholarships-fees-and-finance/scholarships/masters-scholarships.aspx

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This is a full-time research-based postgraduate degree, run jointly by Imperial College London and the Natural History Museum, London. Read more
This is a full-time research-based postgraduate degree, run jointly by Imperial College London and the Natural History Museum, London.

OPEN DAY

visit the course pages for more information about the next Open Day at NHM on Wednesday 7 June 2017.

OUTLINE

Taxonomy and systematics provide the foundation for studying the great diversity of the living world. These fields are rapidly changing through new digital and molecular technologies. There is ever greater urgency for species identification and monitoring in virtually all the environmental sciences, and evolutionary ‘tree thinking’ is now applied widely in most areas of the life sciences. These courses provide in-depth training in the study of biodiversity based on the principles of phylogenetics, evolutionary biology, palaeobiology and taxonomy. The emphasis is on quantitative approaches and current methods in DNA-based phylogenetics, bioinformatics, and the use of digital collections.

LOCATION

The course is a collaboration of Imperial College London (Silwood Park) with the Natural History Museum. This provides an exciting scientific environment of two institutions at the forefront of taxonomic and evolutionary research.

[[SYLLABUS ]]
The MRes in Biosystematics features hands-on research projects that cover the main methodological approaches of modern biosystematics. After 6 weeks of general skills training, students will ‘rotate’ through three research groups each conducting a separate 14-week project in specimen-based phylogenetics, molecular systematics/genomics, and bioinformatics. The projects may be of the student’s own design. Students attend small group tutorials, lab meetings and research seminars.

TRANSFERABLE SKILLS]

The GSLSM (Graduate School of Life Sciences and Medicine) at Imperial College London provides regular workshops covering a wide range of transferable skills, and MRes students are encouraged to undertake at least four during the year. Topics include: Applied Writing Skills, Creativity and Ideas Generation, Writing for Publication, Introduction to Regression Modelling, Introduction to Statistical Thinking.

RECENT PROJECTS

MORPHOLOGICAL

The Natural History Museum’s Dorothea Bate Collection of dwarfed deer from Crete: adaptation and proportional size reduction in comparison with larger mainland species
Cambrian lobopodians and their position as stem-group taxa
Atlas of the Caecilian World: A Geometric Morphometric perspective
Tooth crown morphology in Caecilian amphibians
Morphometrics of centipede fangs: untapping a possible new source of character data for the Scolopendromorpha
Phylogeny of the Plusiinae (Lepidoptera: Noctuidae): Exploring conflict between larvae and adults
A comparison between species delineation based on DNA sequences and genital morphometrics in beetles (Coleoptera)

MOLECULAR

Geographical distribution of endemic scavenger water beetles (Hydrophilidae) on the island of Madagascar based on DNA sequence data
Cryptic diversity within Limacina retroversa and Heliconoides inflate
Phylogenetics of pteropods of the Southern Oceans
Molecular discrimination of the European Mesocestoides species complex
A molecular phylogeny of the monkey beetles (Coleoptera: Scarabaeidae: Hopliini)
The molecular evolution of the mimetic switch locus, H, in the Mocker Swallowtail Papilio dardanus Brown, 1776
Phylogenetic and functional diversity of the Sargasso Sea Metagenome

BIOINFORMATICS

A study into the relation between body size and environmental variables in South African Lizards
Cryptic diversity and the effect of alignment parameters on tree topology in the foraminifera
Delimiting evolutionary taxonomic units within the bacteria: 16S rRNA and the GMYC model
Testing the molecular clock hypothesis and estimating divergence times for the order Coleoptera
Taxon Sampling: A Comparison of Two Approaches
Investigating species concepts in bacteria: Fitting Campylobacter and Streptococcus MLST profiles to an infinite alleles model to test population structure
Assessing the mitochondrial molecular clock: the effect of data partitioning, taxon sampling and model selection

ON COMPLETION OF THE COURSE, THE STUDENTS WILL HAVE:

• a good understanding of the state of knowledge of the field, together with relevant practical experience, in three areas of biosystematic science in which he or she has expressed an interest;
• where applicable, the ability to contribute to the formulation and development of ideas underpinning potential PhD projects in areas of interest, and to make an informed decision on the choice of potential PhD projects;
• a broad appreciation of the scientific opportunities within the NHM and Imperial College;
• knowledge of a range of specific research techniques and professional and transferable skills.

FURTHER INFORMATION

Students are encouraged to view the NHM website for further information, and to contact the course administrator if they have any queries. Visits can be arranged to the NHM to meet the course organisers informally and to be given a tour of the facilities. Applications should be made online on the Imperial College London website.

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This programme is for students who are passionate about early life, dinosaurs, mass extinctions, macroevolution, fossil preservation and understanding the palaeobiology of extinct organisms. Read more
This programme is for students who are passionate about early life, dinosaurs, mass extinctions, macroevolution, fossil preservation and understanding the palaeobiology of extinct organisms. It examines quantitative aspects of the fossil record and the history of life. The research-oriented MSc bridges the biology-geology divide and will provide you with a strong background for independent research to PhD level or for a career in museums, libraries, management or the media.

This interdisciplinary programme is taught mainly in the School of Earth Sciences, along with some archaeology and biology units. You will engage in current debates in evolutionary biology, systematics and palaeobiology.

You will learn how to analyse problems quantitatively, and design experimental approaches to resolving questions in macroevolution and in the study of ancient organisms. First-hand training in research methods in palaeobiology involves laboratory techniques. In addition, you will learn a range of advanced skills throughout the programme, such as computer software use, numeracy, planning research, problem-solving and communication skills. You will learn multimedia techniques, including presentation of palaeontological data through talks, posters and formal written reports. A key aspect of the programme is preparing your projects for publication, and we provide continuing support to ensure as many projects as possible are published in leading international journals.

Programme structure

The first half of the programme consists of lectures, practical classes, tutorials and visiting speakers, designed to provide a firm foundation in the theory and methodology of the subject.

The programme comprises five core units which all students take, and a number of optional units of which students choose four. We recommend that biologists take some of the more geologically-orientated optional units, and that geologists take some of the biological optional units.

Core units
-Current Controversies in Palaeobiology and Macroevolution
-Scientific Communication
-Phylogenetic Methods in Palaeobiology
-Literature Review
-Research Methods in Palaeobiology

Optional units
-Biomechanics and Functional Morphology
-The Cambrian Explosion: the origin of animal body plans
-Early Human Origins
-Evolutionary Biology*
-Evolution of the Biosphere
-Geology for Research Palaeobiologists**
-Micropalaeontology
-Tree of Life
-Vertebrate Palaeobiology and Evolution

*Mandatory for non-biologists
**Mandatory for non-geologists

Careers

The degree is research-based, and about half the graduates go on to academic careers, usually starting with a PhD. The MSc is focused on methods, and you will learn the latest techniques in phylogenetics, biomechanics, and macroevolution training, which is highly sought after by PhD supervisors across the world.

The training in professional skills, including writing scientific papers, is also highly regarded. Some students have used the MSc as a means to go on to careers in museums, the media and education and now hold senior positions as curators and collection managers in national and regional museums. Graduates also work in making scientific documentaries, or are involved in science education at all levels.

Finally, some graduates have gone into commercial work in marketing, the oil industry and computing, where their practical skills in palaeobiology and communication have proved invaluable.

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What is the Master of Bioinformatics all about?.  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. Read more

What is the Master of Bioinformatics all about?

 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.

Structure

This interdisciplinary two-year programme focuses on acquiring

  • basic background knowledge in diverse disciplines belonging to the field of bioinformatics, including statistics, molecular biology and computer science
  • expert knowledge in the field of bioinformatics
  • programming skills
  • engineering skills

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).

Is this the right programme for me? 

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!

Objectives

The student:

  • Possesses a broad knowledge of the principles of genetics, biochemistry and molecular and cellular biology that underlie the model systems, the experimental techniques, and the generation of data that are analysed and modelled in bioinformatics.
  • Possesses a broad knowledge of the basic mathematical disciplines (linear algebra, calculus, dynamical systems) that underlie mathematical and statistical modelling in bioinformatics.
  • Masters the concepts and techniques from information technology (database management, structured and object-oriented programming, semantic web technology) for the management and analysis of large amounts of complex and distributed biological and biomedical data.
  • Masters the concepts and techniques from machine learning and frequentist and Bayesian statistics that are used to analyse and model complex omics data.
  • Has acquired knowledge of the core methods of computational biology (such as sequence analysis, phylogenetic analysis, quantitative genetics, protein modelling, array analysis).
  • Has advanced interdisciplinary skills to communicate with experts in life sciences, applied mathematics, statistics, and computer science to formalise complex biological problems into appropriate data management and data analysis strategies.
  • Can - in collaboration with these experts - design complex omics experiments and analyse them independently.
  • Can independently collect and manage data from specialised literature and public databases and critically analyse and interpret this data to solve complex research questions, as well as develop tools to support these processes.
  • Investigates and understands interaction with other relevant science domains and integrate them within the context of more advanced ideas and practical applications and problem solving.
  • Demonstrates critical consideration of and reflection on known and new theories, models or interpretation within the specialty; and can efficiently adapt to the rapid evolution the life sciences, and especially in omics techniques, by quickly learning or developing new analysis strategies and incorporating them into the learned competences.
  • Presents personal research, thoughts, ideas, and opinions of proposals within professional activities in a suitable way, both written and orally, to peers and to a general public.
  • Develop and execute original scientific research and/or apply innovative ideas within research units.
  • Understands ethical, social and scientific integrity issues and responsibilities and is able to analyse the local and global impact of bioinformatics and genomics on individuals, organisations and society.

Career paths

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.

 



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Goal of the 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 (. Read more

Goal of the 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:

  • Have first class knowledge and capabilities for a career in life science research and in expert duties in the public and private sectors
  • Competence to work as a member of a group of experts
  • Have understanding of the regulatory and ethical aspects of scientific research
  • Have excellent communication and interpersonal skills for employment in an international and interdisciplinary professional setting
  • Understand the general principles of mathematical modelling, computational, probabilistic and statistical analysis of biological data, and be an expert in one specific specialisation area of the LSI programme
  • Understand the logical reasoning behind experimental sciences and be able to critically assess research-based information
  • Have mastered scientific research, making systematic use of investigation or experimentation to discover new knowledge
  • Have the ability to report results in a clear and understandable manner for different target groups
  • Have good opportunities to continue your studies for a doctoral degree

Further information about the studies on the Master's programme website.

Pro­gramme con­tents

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 algorithmicsCombinatorial 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 bioinformaticsjointly 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 GeneticsComputational 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 BiomedicumThe 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.



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