PhD position Reduction of uncertainty in models of biochemical networks
University of Groningen
Faculty of Mathematics and Natural Sciences
The Molecular Systems Biology group at the University of Groningen has a number of openings for enthousiastic and talented PhD students. The University of Groningen located in the north of the Netherlands enjoys an international reputation as one of the oldest and leading research universities in Europe.
The Molecular Systems Biology group lab hosts the group of Prof Matthias Heinemann and the group of Dr Andreas Milias-Argeitis. Prof Heinemann is mainly interested in generating a quantitative understanding about core (microbial) metabolism, and Dr Milias-Argeitis focuses on developing combined computational/experimental methods for the design of dynamic external input signals, which can potentially extract more information from a system interest in comparison to constant perturbations. The positions described below are provided by Dr Milias-Argeitis.
Uncertainty permeates every aspect of modeling in systems biology: sparse and noisy experimental data lead to poorly inferred parameters, while incomplete biological mechanistic knowledge results in structural ambiguities. Consequently, model predictions typically display large variability that complicates further validation and analysis steps. In this project, we aim to develop computationally efficient methods for uncertainty quantification in deterministic and stochastic dynamical models of biochemical networks by combining non-parametric Bayesian models with efficient methods for uncertainty propagation. The developed methods will be used to evaluate the effect of different dynamic input perturbations on the reduction of prediction uncertainty, with the goal of determining experiments that can maximize the information about particular aspects of a given system.
Tools and methods that candidates will learn: Dynamical systems theory, stochastic processes, Bayesian statistics, Monte Carlo methods for inference. The opportunity to actually perform dynamic perturbation experiments on systems of interest using optogenetics will also be provided.
Candidates should have a background in one of the fields of (computational) systems biology, applied mathematics, (control) engineering or physics, and ideally have some undergraduate research experience. They should have good knowledge of programming (e.g. in Matlab, Python or C++) and experience with dynamical system simulation. Some familiarity with stochastic process theory (Markov processes) and uncertainty quantification methods is a plus. The candidates should have good command of English (oral and written) and possess excellent communication and collaboration skills.
Conditions of employment
Contract length: 48 months.
The University of Groningen offers a salary of € 2,174 gross per month in the first year up to a maximum of € 2,779 gross per month in the fourth year. It is a temporary assignment for a period of four years. First, you will get a temporary position of one year with the perspective of prolongation with another three years. Before the end of the first year, an evaluation will take place as to the feasibility of successful completion of the PhD thesis within the next three years. The preferred starting date is earliest December 2016, but the position remains open until a candidate is identified. How to apply We are looking for excellent and highly motivated candidates. Their applications should contain: (i) a CV, (ii) information about grades and other measures of success, (iii) two letters of recommendation, (iv) a statement on how the candidate’s prior experience/expertise could be connected to one of the above mentioned projects. You may apply for this position until 16 October / before 17 October 2016 Dutch local time by means of the application form (click on "Apply" below on the advertisement on the university website). Unsolicited marketing is not appreciated.
Maximum salary: 2779.
For additional information, please contact:
Dr Andreas Milias-Argeitis
In your application, please always include the job opening ID 216250
Extra informatie kan worden verkregen via een van de volgende links:
About the group
Digital application form