Post-Doctoral position in stochastic modelling of drug …, Bern

Post-Doctoral Position in Stochastic Modelling of Drug Resistance

A post-doctoral collaborator is sought for a joint project between the Institute of Mathematical Statistics and Actuarial Science (IMSV), University of Bern, and the Department of Visceral Surgery&Medicine, Bern University Hospital. The project focuses on stochastic processes and statistical estimation challenges in medical problems related to drug resistance. Duration and occupation rate:

18 months at 100% (negotiable) The project investigates stochastic resetting strategies for therapy changes to prevent drug resistance development, utilizing theories of stochastic processes, stochastic differential equations, stochastic simulation, and Bayesian analysis. The collaborator will be mentored by an interdisciplinary team from statistics (Profs. Riccardo Gatto and David Ginsbourger) and medicine (Prof. Deborah Stroka and Dr. Daniel Sanchez Taltavull). Interaction with Ph.D. and Master students is expected. The position is hosted at IMSV.Candidate Requirements: Ph.D. in probability/statistics, mathematical biology/physics, or related fields Excellent written and oral English communication skills Ability to work independently in an international, collaborative environment with Ph.D. and Master students In-depth knowledge of at least one of the following: stochastic differential equations, simulation of rare events, Bayesian inferenceProficiency in programming languages such as R or Python and scientific computing Interest or background in biology and/or epidemiology is a plus What we offer: A vibrant scientific environment with opportunities to impact science and society at a high-level university A competitive salary Good work-life balance in the city of Bern, known for its high quality of lifeStarting date:

As soon as possible Salary:

According to University of Bern guidelines Interested candidates should send their CV and two references to: R. Gatto,



(+41 31 684 8807) Applications received before January 15, 2022, will be fully considered. Later applications will be reviewed until the position is filled.

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