The Department of Biosciences, Department of Computer Science and Institute of Biotechnology, at the University of Helsinki, invite applications for a two year
POSTDOCTORAL RESEARCHER POSITION in MACHINE LEARNING 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 experimentalists1-5.
We are now seeking a highly motivated researcher with strong quantitative skills to apply and develop machine learning methods for:
• Evolutionary prediction and control 1,2
• Biomedical applications of Big Data 3,4
• Characterisation of drug resistance 5
The ideal candidate will have extensive experience in genomic data analyses, machine learning and evolution. However, as our research is cross-disciplinary it is possible to contribute coming from several different fields. Thus, we welcome applications from exceptional candidates, with a quantitative background, from other fields. It is also important for the candidate to have strong programming skills and experience in working with large data sets.
Knowledge, skills and experience required: E = Essential, D = Desirable
• PhD in a relevant subject area (Physics, Mathematics, Computer Science, Engineering, Statistics, Computational Biology, Bioinformatics, Genetics, Molecular Biology) (E)
• Ability to develop novel quantitative models and read mathematical literature (E)
• Experience in formulating statistical models and applying them to real data (D)
• Full working proficiency in a scripting language (e.g. Python, R, Perl) and UNIX/Linux (E), and in a compiled language (e.g. C, C++) and cluster based computing (D)
• Ability to work independently, organise workload, and communicate ideas and results (E)
• Strong publishing record (E)
• Knowledge of genomics and molecular biology (D)
• Proven record in problem solving, data analysis and generation of novel ideas (D)
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