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.
Evolution of transcriptional regulation
The Flicek research group develops 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.
Computational cancer biology
The Gerstung group develops statistical models and bioinformatics tools for understanding cause and consequence of cancer genomes. They create models for relating different layers of genomic, molecular and clinical data to extract the precise connections among variables to understand the connection of genotype and phenotype. They also develop biostatistical models and informatics tools for predicting outcome based on comprehensive high-dimensional datasets. They also study the evolutionary dynamics of cancer, developing accurate biooinformatics tools to accurately detect subclonal mutations and reconstruction of phylogenies.
Computational modelling and informatics for drug discovery
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.
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.
Our group develops bioimage analysis tools that blend continuous mathematical models and computer vision (e.g., learning-based) algorithms. We are interested in flexible contour representations that allow identifying and precisely characterizing biological objects in a large variety of image data. These models can then be applied to quantify phenotypical variations at the single-cell or single-individual level in experiments ranging from genome-wide knockout screens to population dynamics studies.
We are recruiting students who have a good background in computer vision and image processing, with interests in optimisation, approximation and sampling theory. Our group will start at EMBL-EBI on 15 September 2018.