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 research groups that are currently accepting PhD students at EMBL-EBI. You can find other EMBL research units on the EMBL website, and browse all EMBL research groups in our Research at a Glance brochure.
Functional genomics and analysis of small RNA function
Dr Anton Enright's research group aims to predict and describe the functions of genes, proteins and regulatory RNAs as well as their interactions in living organisms. Regulatory RNAs have recently entered the limelight, as the roles of a number of novel classes of non-coding RNAs have been uncovered. The group's work involves the development of algorithms, protocols and datasets for functional genomics. The focus is on determining the functions of regulatory RNAs including microRNAs, piwiRNAs and long non-coding RNAs. The Enright group collaborates extensively with experimental laboratories on commissioning experiments and analysing experimental data.
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Drug discovery informatics
The ChEMBL team, led by Dr John Overington, develops and manages EMBL-EBI’s database of quantitative small molecule bioactivity data focussed in the area of drug discovery. Although great progress has been made in developing biological drugs, synthetic small molecule and natural product-derived drugs still form the majority of novel life-saving drugs. The process complexity and costs of discovering new drugs has recently risen to the point where public-private partnerships are coming to the fore. Central to this is data sharing and availability of structure, binning, functional and ADMET data). The ChEMBL database stores curated two-dimensional chemical structures and abstracted quantitative bioactivity data alongside calculated molecular properties. The majority of the ChEMBL data is derived by manual abstraction and curation from the primary scientific literature, and therefore cover a significant fraction of the structure–activity relationship (SAR) data for the discovery of modern drugs. Our associated research interests focus on data-mining ChEMBL data applied to drug-discovery challenges.
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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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Small molecule metabolism in biological systems
Dr Christoph Steinbeck leads the Cheminformatics and metabolism service team, which runs a number of key services and develops algorithms to: process chemical information; predict metabolomes based on genomic and other information; determine the structure of metabolites by stochastic screening of large candidate spaces; and enable the identification of molecules with desired properties. This requires algorithms based on machine learning and other statistical methods for the prediction of spectroscopic and other physicochemical properties represented in chemical graphs. Dr Steinbeck also has a research group, which focuses on the understanding of the small-molecule metabolism of living organisms. The group is interested in the analysis of metabolomics experiments, including methods for computer-assisted structure elucidation of biological metabolites and metabolic pathways. They develop and maintain chemistry-related databases of biological interest, and develop machine-learning methods for the prediction of mass (MS) and nuclear magnetic resonance (NMR) spectra for use in rereplication and structure elucidation. The methods and algorithms developed in the group are available through an open-source library for structural chemo- and bioinformatics.
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Cheminformatics and metabolism
The Cheminformatics and metabolism team, led by Dr Christoph Steinbeck, provides the biomedical community with information on metabolism: small molecules and their interplay with biological systems. We develop and maintain MetaboLights, a metabolomics reference database and study data repository; ChEBI, EMBL-EBI’s database and ontology of chemical entities of biological interest. We also develop the biochemical reaction database Rhea jointly with the Swiss Institute of Bioinformatics. In support of our mission to create a comprehensively document the metabolomes of organisms and how they change with fluctuations in the exposome, we started and coordinate the European FP7 project COSMOS for the Coordination of Standards in Metabolomics.
Our team develops methods to decipher, organise and publish the small molecule metabolic content of organisms. We also develop algorithms to: process chemical information; predict metabolomes based on genomic and other information; determine the structure of metabolites by stochastic screening of large candidate spaces; and enable the identification of molecules with desired properties. This requires algorithms based on machine learning and other statistical methods for the prediction of spectroscopic and other physicochemical properties represented in chemical graphs. Dr Steinbeck also has a research group, which focuses on the understanding of the small-molecule metabolism of living organisms.
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Gene expression regulation and protein complex assembly
Dr Sarah Teichmann's research group seeks to elucidate general principles of gene expression and protein complex assembly. They study protein complexes in terms of their three-dimensional structure, structure evolution, and the principles underlying protein complex formation and organization. Another major focus is understanding regulation of gene expression during switches in cell state, and in their wet lab at the Wellcome Trust Sanger Institute the group uses mouse T-helper cells as a model of cell differentiation.
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Proteins: structure, function and evolution
Prof Dame Janet Thornton's research group seeks to understand more about how biology works at the molecular level, with a particular focus on proteins and their 3D structure and evolution. They explore how enzymes perform catalysis by gathering relevant data from the literature and developing novel software tools, which allows for the characterisation of enzyme mechanisms. In parallel, they investigate the evolution of these enzymes to discover how they can evolve new mechanisms and specificities. In close collaboration with colleagues at University College London (UCL), the group investigates ways to improve the prediction of function from sequence and structure and to enable the design of new proteins or small molecules with novel functions, and to understand more about the molecular basis of ageing in different organisms.
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