Programme structure

The iCM PhD programme provides a variety of technical and professional training, to prepare students for diverse scientific careers.

In their first year students will undertake introductory core learning modules and rotation projects allowing them to make informed choices for their main PhD project.

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Rotation projects

Students will choose from the projects on offer for the full PhD and carry out three lab based rotation projects. During each rotation students will write a News and Views article about the project and at the end of the rotation they will present their research to the host labs and the iCM Team.

Training courses

Emphasis will be placed on timely skill development with the majority of core skills training taking place during the first year of study.

Core learning modules will cover four key areas:

• best research practice,
• technical skills,
• presentation skills and personal and
• Professional development.

The core learning modules will include technique workshops and training in critical thinking via interactive tutorial-style courses led by programme supervisors. Further training needs will be identified through Personal Learning and Career Development plans and bespoke training will be tailored to individual needs and delivered throughout the PhD at a time that is appropriate to the individual.

Research projects

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Full time PhD research projects start at the end of March of the first year and will be conducted in a research group that hosted one of the rotation projects.

Students will be primarily embedded in research groups with a strong track record in dissecting cellular mechanisms ranging from:

• anti-microbial resistance,
• stochastic heterogeneity,
• epigenetic and chromatin-based regulation,
• control of gene expression,
• non-coding RNA and RNA processing,
• chromosome structure and segregation,
• cell-cycle and
• cell growth regulation.

All PhD projects are collaborative between two supervisors who have complementary expertise:  one in cell mechanisms and one in quantitative skills.

The definition of ‘quantitative skills’ is broad and includes Computational Data Sciences, Mathematics, Biophysics, Structural Biology, Chemical Biology and Biomaterials. By integrating these different areas into collaborative cross-disciplinary projects we will break new ground in understanding cellular mechanisms pertinent to the biomedical arena.

How to Apply