Lunds universitet, Naturvetenskapliga fakulteten, kemiska institutionen

Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has 40 000 students and 7 400 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

The Faculty of Science conducts research and education within Biology, Astronomy, Physics, Geosciences, Chemistry, Mathematics and Environmental Sciences. The Faculty is organized into nine departments, gathered in the northern campus area. The Faculty has approximately 1500 students, 330 PhD students and 700 employees.

Work description

We are looking for a highly motivated candidate with strong experience of probabilistic modeling, to run a project where Bayesian statistical methods are developed to analyze experimental data interrogating the three-dimensional structure of proteins.  

A central goal in this project is to increase our understanding of how proteins self-assemble to form larger structures using time-resolved experimental data, primarily from small angle scattering (SAS). The candidate will develop Bayesian approaches to infer kinetic models of self-assembly processes from the experimental data. The project will also involve the development of other statistical inference methods coupled to the analysis of SAS data, and additional methods to investigate the structure of mixtures of proteins in solution.  

The position does not require a background in protein science or scattering methods, but candidates interested in applying probabilistic modeling to problems in chemistry and physics are encouraged to apply. 

The project is highly interdisciplinary and involves collaboration with researchers from Lund University, Chalmers University and European Spallation Source.

Qualifications

Mandatory:

  • A PhD in statistics, computer science, machine learning, bioinformatics, biophysics or other relevant fields
  • A strong background in probabilistic methods, with a good understanding of Bayesian statistics
  • Good programming skills and experience of writing programs or advanced scripts in the area of probabilistic modeling
  • Be fluent in English (written and spoken)

Meriting:

  • Background in one or more of the following languages: C++, C, Matlab, Python, R
  • Background with Bayesian graphical networks
  • Background in protein modeling
  • Background in small angle scattering
Type of employment Temporary position longer than 6 months
Contract type Full time
First day of employment 2018-11-01 until 2020-10-31
Salary Monthly salary
Number of positions 1
Working hours 100 %
City Lund
County Skåne län
Country Sweden
Reference number PA2018/2993
Contact
  • Ingemar André, Senior Lecturer, +46 (0) 46 222 44 70
  • My Geborek; HR Officer, +46 (0) 46 222 48 53
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62
  • SACO:Saco-s-rådet vid Lunds universitet, 046-222 93 64
  • SEKO: Seko Civil, 046-222 93 66
Published 10.Sep.2018
Last application date 01.Oct.2018 11:59 PM CET

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