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PhD student in Bioinformatics at KU Leuven (Belgium)

Posted by: Rega Institute - KU Leuven

Posted date: Jun-23-2017

Location: Leuven, BELGIUM

For the Laboratory of Clinical and Epidemiological Virology (Rega Institute) we are looking for a motivated PhD student to perform research in a multidisciplinary team.
STATISTICAL AND COMPUTATIONAL METHODS FOR BAYESIAN PHYLOGENETIC INFERENCE
The Evolutionary and Computational Virology Laboratory at the Division of Clinical and Epidemiological Virology (Rega Institute, KU Leuven) focuses on the evolutionary processes that shape viral genetic diversity. This encompasses large-scale epidemic processes, such as population growth and spatial dispersal (a popular topic in phylogeographic and phylodynamics research), as well as small-scale transmission histories and within-host evolutionary processes, including adaptation and recombination. It is our objective to gain better insights into these evolutionary and population genetic processes and to clarify how they relate to epidemic and disease dynamics. To this aim we plan to focus on statistical and computational developments to analyze the increasing amount of data brought about by massive sequencing studies, mainly in a framework of Bayesian phylogenetic inference, for which our research group holds a strong track record. We also aim to explore the applicability of novel models and statistical inference tools, developed as part of our research, in different fields of research.
Project
This project focuses on new developments ina popular Bayesian phylogenetic inference framework (BEAST:https://github.com/beast-dev/beast-mcmc) and its applications to important evolutionary problems, with a particular focus on infectious diseases.
 
The first part of the project involves the development of an integrated web system and database that allows users to register, upload and retrieve sequence data to and from the database. Each user will be able to determine the sharing policy for the data he/she has provided. Such a system should be easily distributed so that other research groups can deploy it on their own server(s)and put it to use without technical interventions. Further, this system will interface with the BEAST software package to analyze the sequence data in an efficient manner. Additionally, visualization packages typically associated with BEAST, such as FigTree (http://tree.bio.ed.ac.uk/software/figtree/) andSpreaD3 (https://rega.kuleuven.be/cev/ecv/software/SpreaD3) may be incorporated into this system. The candidate is expected to design and implement such a system and determine an appropriate strategy to properly distribute the developed system as an easily installed/deployed software package.
 
In the second part of the project, multiple parallelization ideas will be implemented in the BEAST software package. BEAST is mostly written in Java, with its high-performance computational library, known as BEAGLE, being implemented in C/C++ with specific routines that allow for parallel computing on both multi-core CPU and GPU platforms. Recent developments in the field of phylogenetics have shown that straight forward parallelization approaches do not make sufficient use of current multi-core architectures, both in CPU and GPU applications. The goal of this project is to tackle these issues from both a computational and a statistical perspective. The computational aspect entails the implementation of popular routines typically used in computer architecture, to perform automated load balancing and concurrent evaluation of possible future states in the evaluation of posterior distributions. The usefulness of various look-ahead strategies will be implemented and evaluated against the current state of the art. The statistical aspect on the other hand entails the development and adaptation of novel transition kernels in a Bayesian phylogenetic inference framework. Along with the obtained computational improvements, better-performing transition kernels may aid in reducing runtimes of Bayesian analyses by exploring (posterior) distributions of interest in a more efficient manner.

Profile
The candidate for this PhD position should have a strong quantitative background, and preferably holds a master's degree in computer science / informatics (or equivalent through experience), with an interest in statistics/mathematics and (bio)informatics. The candidate hence needs to be experienced in an object-oriented programming language such as Javaor C/C++. The candidate should be sufficiently proficient in English, motivated to work in a team and publish his/her findings, and willing to travel. 

Offer
The candidate will be able to perform research in a dynamic and multidisciplinary team (computer scientists, data analysts and evolutionary biologists), housed in the brand new facilities of the Rega institute at the University hospital campus, and guided by prolific supervisors. The candidate will be able to contribute to the continued development of the BEAST code base, a software package used by many researchers in the fields of phylogenetics and molecular evolution, and collaborate with top researchers in the field. In particular, this project offers the opportunity to collaborate with Prof. Andrew Rambaut (University of Edinburgh), a world expert in statistical phylogenetics with a strong interest in viral evolution and epidemiology. Prof. Rambaut is the lead developer of many widely used and highly cited software packages in the field of pathogen phylodynamics, such as BEAST, FigTree, TempEst (http://tree.bio.ed.ac.uk/software/tempest/) and Tracer (http://tree.bio.ed.ac.uk/software/tracer /). The collaboration also includes Prof. Marc Suchard (UCLA), who is honored with the Committee of Presidents of Statistical Societies (COPSS) Presidents’ Award, the highest possible achievement in the field for a person of under 40. Prof. Suchard will contribute invaluable expertise in MCMC integration and applied probability techniques. Additionally, at the Division of Clinical and Epidemiological Virology, the candidate will be able to interact with several top researchers in the field of epidemiology, virology and metagenomics, and work on important infectious disease problems from an evolutionary perspective.

Interested?
Please use the university’s job portal when applying for this position and submit a motivation letter, overview of study results and two references (along with contact details).
For more information please contact Prof. dr. Guy Baele, tel.: +32 16 32 12 87, mail: guy.baele(at)kuleuven.be or Prof. dr. Philippe Lemey, tel.: +32 16 32 14 28, mail: philippe.lemey(at)kuleuven.be.
You can apply for this job no later than July 31, 2017 via the 
online application tool at http://www.kuleuven.be/eapplyingforjobs/light/54182826

The full job description can be found again here: https://icts.kuleuven.be/apps/jobs ite/vacatures/54182826
Job Title PhD student in Bioinformatics at KU Leuven (Belgium)
Post Details
Email guy.baele(at)kuleuven.be
Employer's Website rega.kuleuven.be
Category
Job Discipline Job Discipline -> Bioinformatics
Job Classification Job Classification -> Research Associate
Job Type Job Type -> Full-time
Location Leuven, BELGIUM
Key Words PhD student, bioinformatics, computer science
Start Date October 1st, 2017
Deadline Jul-31-2017