PhD position in Mathematical Biology: MPI 2171 views

The Research Group Stochastic Evolutionary Dynamics at the Max Planck Institute for Evolutionary Biology is inviting applications for a PhD student (m/f/d) in Mathematical Biology (3 years). The title of the project is “Evolutionary dynamics of antibiotic resistance on plasmids”.

About the position:
  • The position is part of a DFG-funded Research Training Group (RTG) on “Translational Evolutionary Research”.
  • The program brings together 14 research groups from several institutions to study how insights from evolutionary biology can be applied to solve problems in medicine, food production, and wildlife conservation.
  • Projects are organised in tandems who work on related topics. The tandem partner of the proposed project is Professor Tal Dagan (University of Kiel).
  • The student would hence closely interact with a research group that focuses on experimental evolution and data analysis.

Requirements:

  • Applicant must be interested in applying mathematical modeling to gain insights into biological problems and is enthusiastic about math as well as about biology.
  • Applicant will have to learn how to set up and analyse theoretical models to describe biological processes and become skilled in using branching process theory as a modeling tool.
  • Applicants should have a background in Mathematics, Physics, Biology, Computer Science or a related field.
  • Good quantitative skills are essential. Prior experience in mathematical modeling and knowledge of a programming language (C, C++, Java, R, Python) is an advantage.

Applications:

Application to be sent via email to uecker@evolbio.mpg.de including:

  • Motivation letter
  • CV
  • Copies of certificates
  • Contact details of two references
  • Use the code PhD2019-2 in the subject line.
—————–Quick Overview————-
Organization Max Planck Institute for Evolutionary Biology
Country Germany
Fellowship Level Doctoral
Subject areas Mathematics, Physics, Biology, Computer Science
Fellowship amount Varies
Eligibility Open to all nationalities
Deadline December 15, 2019
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