International PhD Programme research topics

When you apply for the EMBL International PhD Programme, you are asked to select two EMBL research groups and to indicate up to four research areas that interest you. A variety of backgrounds - such as biology, chemistry, computational science, mathematics and statistics - are relevant to PhD projects at EMBL-EBI. As well as purely computational projects, there may also be possibilities to incorporate some experimental biology in collaborating laboratories.

Here, we show a provisional list of available PhD projects at EMBL-EBI which are available during the Summer  recruitment 2016 round.

You can find other EMBL research units on the EMBL website, and browse all EMBL research groups in our Research at a Glance brochure.


Application for Summer Recruitment 2016 is now closed. Our next call will open in August 2016.

Flicek research group

Evolution of transcriptional regulation

Dr Paul Flicek's research group focuses on computational models for genome annotation and evolution based on models incorporating DNA-protein interactions, epigenetic modifications, and the DNA sequence itself. The group is also interested in the large-scale infrastructure required for modern bioinformatics including storage and access methods for high-throughput sequencing data.

Contact Flicek research group

Marioni research group

Computational and evolutionary genomics

Dr John Marioni's research group develops effective statistical and computational methods for analysing the vast amounts of data generated in high-throughput experiments. To gain a deeper understanding of complex biological processes such as gene regulation, the group develops computational methods for interrogating high-throughput genomics data. Their work focuses primarily on modelling variation in gene expression levels in different contexts: between individual cells from the same tissue; across different samples taken from the same tumour; and at the population level where a single, large sample of cells is taken from the organism and tissue of interest. Working with experimental colleagues within and beyond EMBL, the group applies their methods to biological questions ranging from the regulation of mammalian gene expression levels to the brain development in a marine annelid.

Contact Marioni research group

Stegle research group

Statistical genomics and systems genetics

Dr Oliver Stegle's research group uses computational approaches to unravel the genotype--phenotype map on a genome-wide scale. Their work focuses on the development and use of statistical methodology to dissect the causes of molecular variation. The group has shown how comprehensive modelling can greatly improve the statistical power to find genetic associations with gene expression levels and provide for an enhanced interpretation of the interplay between genetic variation, transcriptional regulation and molecular traits. The address these methodological questions in the context of close collaborations with experimental groups, where they apply novel statistical tools to study molecular traits in model organisms, plant systems and biomedical applications.

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Steinbeck research group

Small molecule metabolism in biological systems

The Steinbeck Research Group aims to understand how the exposome and metabolome interact. This entails the analysis of advanced multi-omics phenotypic data sets, with an emphasis on metabolomics and with chances of stepping into systems biology scale models. The group has a track record in different areas of cheminformatics and bioinformatics related to metabolism, such as structure elucidation, metabolic model reconstruction, prediction of spectroscopic and other physicochemical properties represented in chemical graphs and machine learning methods applied to mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectra data among others. Students and researchers at the group benefit from the close interaction with the Steinbeck Service team, which is one of the world leaders in the provision of metabolomics and small molecule data and metabolomics standards, and from its extended network of collaborators in metabolism related research.

Contact Steinbeck research group