Evolutionary Genetics & Genomics MSc

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Evolutionary Genetics & Genomics MSc

  • Objectives The aim of this course is to provide the conceptual evolutionary background and training in large-scale data handling skills, particularly the use of statistical and computational approaches, to enable students to undertake evolutionary genetics and genomics research at the cutting edge.
  • Entry requirements Entry requirements: Applicants will need to hold a First or Upper Second class honours degree, or the overseas equivalent, in a biology or physical sciences subject. In certain circumstances, a Lower Second class honours degree supplemented with appropriate relevant work experience may be acceptable.
  • Academic title Evolutionary Genetics & Genomics MSc
  • Course description Course description

    Evolutionary genetics can used to address a wide range of exciting research questions in molecular evolution, genome evolution, adaptation, speciation, conservation, the evolution of form, species relationships, etc.

    The course director is Dr Cathy Walton.

    Module details

    Introduction to core concepts and development of data-handling skills: A core module will cover the fundamental principles of evolutionary genetics and genomics. The application of these principles to research questions will be illustrated using case studies often involving the students in data handling and problem solving sessions. There will also be a taught course to introduce the students to statistical approaches routinely used in evolutionary genetics.

    Research projects: Engaging in full-time research in active laboratories is the key part of this programme. Research projects can be empirical (laboratory-based or bioinformatics) or theoretical. All empirical projects will involve a data-handling component to enable students to hone their analytical skills. Each student will undertake two full-time research projects. The strength of evolutionary genetics research in Manchester allows us to offer students an exceptionally broad and exciting range of options.

    Teaching and learning
    Lectures, tutorials, data handling/problem solving sessions, seminar series, poster and oral presentations, research projects.

    Progression and assessment
    Student assessment will be based on the research component of the course (67% of total marks) based on the two projects, and the taught component of the course (33% of total marks) in the form of continuous assessment, examinations and write-ups of seminars.

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