International PhD Programme research topics
When you apply for the EMBL International PhD Programme, you are asked to select two EMBL research units 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.
The following Group Leaders at EMBL-EBI are hoping to recruit PhD students in the ongoing round.
Sequence algorithms and intra-species variation
The Birney research group focuses on sequence algorithms--notably theoretical and practical implementations of data compression techniques--and using intra-species variation to explore elements of basic biology. They study the interplay of natural DNA sequence variation with cellular assays and basic biology, and collaborate with the Goldman group on a method to store digital data in DNA molecules.
Contact the Birney research group
Functional genomics research
The Brazma research group complements the Functional Genomics service team, developing new methods and algorithms and integrating new types of data across multiple platforms. The group is particularly interested in cancer genomics and transcript isoform usage, and collaborates closely with the Marioni group and others throughout EMBL.
Contact the Brazma research group
Computational approaches to understanding microbiomes
The Finn research group focuses on developing computational approaches for the reconstruction of genomes from metagenomes, thereby enriching the tree of Life. The group will also investigate the distribution of microbes and functions in different environments, and probe the functions of so-called ‘microbial dark matter’.
Contact the Finn research group
Developing computational methods for representing genetic variation, and using them to study bacteria and parasites.
The Iqbal group develops computational methods for representing the full breadth of genetic variation, and applies these methods to real data, for example M. tuberculosis, S. aureus, E. coli and P. falciparum. Their translational work focuses on applying whole-genome sequencing to pathogens in a clinical setting. They have developed an application for predicting antibiotic resistance, and develop pathogen variation data resources to enable strain and resistance surveillance.
Contact the Iqbal research group
We are interested in the development and evaluation of methodologies, tools and understanding that contribute to the discovery and development of new medicines using computer modelling and informatics methods.Some of this work builds on the widely-used ChEMBL chemogenomics resources that our associated service team develops, and aims to address questions such as target selection, molecule design and predicting safety/toxicity.
Contact the Leach research group
Creating predictive and conditional whole cell signaling models
The Petsalaki group studies human cell signaling with the aim of creating predictive and conditional whole-cell signaling models. Using these models, we seek to gain insights into basic cell functions and disease mechanisms in order to aid the design of therapeutic approaches or biomarker discovery for patients with specific proteome, expression or genome profiles.
Contact the Petsalaki research group
Cis-regulatory networks and interactions
The Zerbino group is focused on developing efficient computational methods to transform large genome-wide datasets into a map of transcriptional regulation. Using evolutionary signatures, genetic markers, epigenomic marks, and chromatin structure, we aim to derive the elusive traces of transcriptional regulation.
In particular, we aim to leverage the power of high-throughput processing and novel machine learning techniques to integrate large collections of available experiments and better understand the mechanisms of gene expression regulation. Better knowledge of regulatory elements on the genome is of huge importance both for molecular biology and translational biomedical applications. These genomic elements have been demonstrated to be critical in understanding development, common as well as Mendelian traits and diseases, and evolution. Having a detailed and well understood map of regulatory regions and networks will allow us to gain higher confidence in determining the aetiology of diseases and help accelerate medical research.
Contact the Zerbino research group
EMBL-EBI - NIHR Cambridge Biomedical Research Centre collaboration
Some projects are part of the EMBL-EBI - NIHR Cambridge Biomedical Research Centre collaboration.
The European Bioinformatics Institute (EMBL-EBI) and NIHR Cambridge Biomedical Research Centre (BRC) are building on the collaborative relationship between the two institutes. Graduate students will be full members of the EMBL International PhD programme, will be registered as students of the University of Cambridge, and will work across both institutes on collaborative projects with supervision from members of faculty from EMBL-EBI and from the Cambridge BRC. Projects will be broadly related to translational clinical research projects involving human subjects.
The National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC) is a partnership between University of Cambridge and Cambridge University Hospitals (CUH). It was established in 2007, and has recently been re-designated as a NIHR Biomedical Research Centre with an award of £114.3m over the next five years. The Cambridge Biomedical Research Centre is based on the Cambridge Biomedical Campus, which combines on a single site scientific research in world-class institutes, patient care in NHS hospitals, and drug discovery in pharmaceutical companies including AstraZeneca and GlaxoSmithKline (GSK). Over the next five years the BRC will undertake translational research in the fields of cancer, cardiovascular and respiratory disease, dementia, disorders of the nervous system and mental health, infections and their resistance to antibiotics, obesity and diabetes, bone disease, digestive disorders and the effect of nutrition, diet and lifestyle on health, transplantation and the use of stem cells to repair tissues, and women's and children’s health.
EBI Group Leader
BRC Group Leader
|Evangelia Petsalaki||Antonio Vidal-Puig||Using human pluripotent stem cells to dissect the signalling and metabolic pathways involved in white and brown adipose tissue differentiation and function|
|Pedro Beltrao||Andras Lakatos||
Regulatory pathway analysis in dysfunctional glia-neuron communication in Motor Neuron Disease
This collaborative project between the Lakatos and Beltrao Labs aims at elucidating novel pathomechanisms in Motor Neuron Disease (MND) with relevance to other neurodegenerative diseases. In specific, we have been focussing on regulatory mechanisms underlying the disruption of glia mediated signaling processes in their interactions with motor neurons, using MND patient derived human induced pluripotent stem cell (hiPSC) systems. The graduate student will apply a state-of-the-art integrated multi-omics strategy with computational methods to identify central and targetable elements in the disease process with a translational outlook.
|Paul Flicek||Steve Charnock-Jones|
|Daniel Zerbino||Patrick Chinnery||Population structure of human mitochondrial variants.
Cell homeostasis is critically dependent upon the production of adenosine triphosphate (ATP) by a group of proteins assembled on the inner mitochondrial membrane. In humans, over 100 proteins are assembled into the five respiratory chain complexes, but the different interlocking peptide components are encoded by two totally distinct genomes. The vast majority of respiratory chain proteins are synthesised from nuclear gene transcripts within the cytosol, but 13 critical components are synthesised within the mitochondrion itself from the small 16.5Kb circular mitochondrial genome (mtDNA). Cell function is therefore critically dependent upon the interaction between mtDNA and nuclear DNA, but the two genomes are inherited in a totally different manner, with mtDNA being inherited exclusively down the maternal line.
Candidate gene, exome and sequencing studies in patients with severe biochemical defects of mitochondrial function have identified mutations in either the mtDNA or nuclear DNA as a cause of inherited mitochondrial diseases. These disorders affect tissues and organs that are critically dependent on ATP synthesis, and resemble common complex traits – including diabetes, cerebrovascular disease, dementia and other neurodegenerative diseases. Intriguingly, there is also emerging evidence from large genetic association studies that complex common diseases are also influenced by more subtle genetic variation in mtDNA and nuclear DNA, with their combined effect altering disease risk. However, at present, most genetic association associations ignore mitochondrial data altogether and avoid dealing with the differences in inheritance patterns between mitochondrial and nuclear DNA.
We propose to compile a reference collection of mitochondrial genotypes, computed from the archived raw data of whole genome and whole exome sequencing experiments. Curated properly for phenotype metadata, this dataset will serve to answer a fundamental question: how much common phenotype variability can be explained by mitochondrial data? Assuming this variability is large enough to warrant further genetic investigation, this dataset would also serve as a reference resource to analyse the mitochondrial component of GWAS experiments.
|Andrew Leach||Vasilis Kosmoliaptsis||Human organ transplantation is one of the most significant medical advances over the past fifty years. The key challenge of organ rejection is tackled through the use of immunosuppressant drugs and techniques that aim to identify the most suitable tissue match between donor and recipient. Nevertheless, despite the undoubted positive impact of organ transplantation on the lives of thousands of patients worldwide, there remain areas where further progress is needed. In this project, we aim to combine our complementary expertise in transplant surgery and computational modelling techniques to capitalise on the greater understanding of the molecular basis of the immunological response and the ever-growing volumes of genetic and clinical outcomes data. Our overall goals are to develop new and improved methods for identifying the most suitable donor-recipient pairs, so leading to improved clinical outcomes and enhanced patient benefit.|