DOCTORAL STUDENT POSITION in COMPUTATIONAL GENOMICS and EVOLUTION28.4.2017
The Department of Biosciences, Department of Computer Science and Institute of Biotechnology, at the University of Helsinki, invite applications for a four year
DOCTORAL STUDENT POSITION in COMPUTATIONAL GENOMICS and EVOLUTION
Evolution connects all living organisms and is the common thread across all of biology. Organisms evolve to better survive in their environments and to adapt to new challenges. This leads to complex dynamical scenarios, which are presently understood only in a limited way. Understanding evolution is one of the most intriguing scientific topics due to its ability to unify often seemingly disjoint fields of biology. Furthermore, quantitative understanding of evolution is a prerequisite to successfully combat pathogens, pests and loss of biodiversity. For instance, identifying genetic variants which contribute to the emergence of drug resistance, a question with importance for the treatment of pathogens, and of cancer, is a challenge of understanding the evolution of these populations. Big Data provide new opportunities to study in detail how populations evolve. However, data alone, without theory and scalable algorithms to extract information from it, is not sufficient to make progress. The Mustonen Group develops computational algorithms and theory to better understand evolution. The work is cross-disciplinary and we have a record of successful research collaborations working together with clinicians and experimentalists.
We are now seeking a highly motivated student with strong quantitative skills to pursue a PhD on one of the following themes:
• Theory and methods for evolutionary prediction and control (1,2)
• Algorithms for biomedical applications of Big Data (3,4)
• Characterisation of the emergence of drug resistance (5)
The ideal candidate will have a quantitative background, genuine interest in Biology and Evolution, programming skills and some experience in working with large data sets.
Requirements for the Ph.D. student are:
• M.Sc. in a relevant subject area (Physics, Mathematics, Computer Science, Engineering, Statistics, Computational Biology, Bioinformatics, Genetics, Molecular Biology)
• Proven academic ability
• Strong motivation, drive and curiosity
Please submit your application as a single pdf file which includes:
• CV with possible publications listed
• a copy of your transcript records (i.e. printout of the courses completed during MSc)
• contact details of two references (e.g. MSc thesis supervisors)
• a cover letter with a description of your research interests
The salary for four years (3-month probation period) is based on levels 2-4 of the job requirement scheme for teaching and research personnel in the salary system of Finnish universities (2100-3300€/month (gross)). The appointee shall be paid a salary component based on personal work performance.
To apply, please submit your application using the University of Helsinki electronic recruitment system by clicking on Apply for job. Internal applicants (i.e. current employees of the University of Helsinki) must submit their applications through the SAP HR portal. Apply at latest on 28th of May 2017, the start date is negotiable.
For more information, please contact Prof. Ville Mustonen (email@example.com).
1. Lässig M, Mustonen V, Walczak AM (2017) Predicting Evolution. Nature Eco Evol 1:0077.
2. Fischer A, Vázquez-García I, Mustonen V (2015) The value of monitoring to control evolving populations. Proceedings of the National Academy of Sciences 112(4):1007–1012.
3. McKerrell T, et al. (2016) Development and validation of a comprehensive genomic diagnostic tool for myeloid malignancies. Blood. doi:10.1182/blood-2015-11-683334.
4. Fischer A, Vázquez-García I, Illingworth CJR, Mustonen V (2014) High-definition reconstruction of clonal composition in cancer. Cell Reports 7(5):1740–1752.
5. Vázquez-García I, Salinas F, Li J, Fischer A, Barré B, Hallin J, Bergström A, Alonso-Perez E, Warringer J, Mustonen V, Liti G Background-dependent effects of selection on subclonal heterogeneity. http://dx.doi.org/10.1101/039859
Apply at latest 28.05.2017
Sunday, May 28, 2017