Two PhD positions in bioinformaticsFully-funded 3 year position, starting as soon as possible
This project, funded by the Swiss National Priority Programme "Big Data", aims at developing robust comparative genomic analyses that take advantage of abundant but low-quality genomic and transcriptomic data.
Making sense of genome and transcriptome data relies on comparative genomics to identify the conserved or divergent elements, and elucidate the ones that are associated with essential housekeeping functions and those associated with innovation or adaptation. For instance, an important question is whether a gene has the same function in a model organism such as fly or mouse and in humans. However, this simple question leads to complex methodological issues. Finding the corresponding ("orthologous") genes in different species is not trivial computationally and is dependent on the quality of the data. Characterizing differences between orthologous genes as functionally relevant is also computationally intensive and dependent on data quality.
In this project, we aim to develop a comparative genomics approach that leverages the abundant but noisy and heterogeneous data generated, and models coevolution of multiple genes in functional modules such as metabolic pathways. To achieve this, we will:
- combine high- and low-quality genomic data available, with an emphasis on robustness to data incompleteness and inaccuracies, and scalability to tens of thousands of genomes.
- implement stringent quality controls-via statistical tests, empirical benchmarks, and filters.
- develop efficient machine learning algorithms that can cope with orders of magnitude more data.
The project is a collaboration among the groups of Prof. Nicolas Salamin, Prof. Marc Robinson-Rechavi and Prof. Christophe Dessimoz at the University of Lausanne, and Prof. Bastien Chopard at the University of Geneva.
The first PhD student will focus on the orthology and sequence alignments aspects of the project under the guidance of Profs Dessimoz and Robinson-Rechavi. The second PhD student will focus on detecting co-evolution in genes and pathways under the guidance of Profs Salamin and Chopard. Both PhD students will be based at the University of Lausanne, with a joint affiliation with the Swiss Institute of Bioinformatics. They will be provided with strong mentorship and be given ample scientific training opportunities.
Working conditions in Lausanne are extremely competitive, and include access to state-of-the-art computing and sequencing facilities. The environment is highly international, and all activities are conducted in English.
- Master degree in quantitative discipline (bioinformatics, computer science, statistics, mathematics, or related subjects)
- Demonstrated programming skills
- Effective spoken and written English communication skills
- High level of motivation
- Ability to collaborate in an interdisciplinary environment
- Prior experience in computational biology research
- Prior experience in high-performance computing and/or machine learning
- Prior experience in evolutionary biology
How to applyThe application should consist of a single PDF file containing the following elements:
- Motivation letter
- Curriculum vitae
- Copy of university diplomas and transcripts
- The names and contact details of 2-3 references
Applications should be sent to Prof. Christophe Dessimoz (Christophe.Dessimoz@unil.ch) with subject line "Big data PhD job".
To ensure full consideration, applications should be received by 10 Dec 2016