Postdoctoral Position in Bayesian Inference for Cell Biology Applications
Postdoctoral Position in Bayesian Inference for Cell Biology Applications
Uppsala University
Uppsala, Sweden
Duties
Technological advances in molecular staining and cell imaging have resulted in a multitude of spatio-temporal cell imaging data. These data hold rich information about how cells act and interact. In this research project, we are developing mathematical and probabilistic models that quantify cell actions and cell-to-cell interactions from dynamic point patterns (where points represent cell coordinates) that are extracted from imaging data.
The postdoctoral researcher’s main task will be to develop Bayesian inference methods and computational pipelines designed to estimate mathematical models from dynamic point pattern data. Model inference will mainly be done using a probabilistic programming framework, such as Stan.
Moreover, the postdoctoral researcher will:
- collaborate with a multidisciplinary team of experts in mathematics, statistics, machine learning and pre-clinical cancer research,
- lead the writing of scientific manuscripts and present their work at international conferences,
- have the opportunity to teach (up to 20%),
- have the opportunity to supervise students.
The postdoctoral researcher will join the Artificial Intelligence and Mathematics for Oncology (AIMOn) group.
Requirements
PhD degree in Applied Mathematics, Statistics, Machine Learning, Biophysics, or a related subject or a foreign degree equivalent to a PhD degree in one of the aforementioned subjects. The degree needs to be obtained by the time of the decision of employment. Those who have obtained a PhD degree three years prior to the application deadline are primarily considered for the employment. The starting point of the three-year frame period is the application deadline. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.
Applicants should be team players with excellent communication skills. Mathematical problem solving and programming skills are required. No previous knowledge of cancer biology is required but applicants should have a genuine interest in using mathematical, probabilistic and computational methods to better understand cancer.
Additional qualifications
Research experience in one or more of the following subjects is meriting (without order of importance):
- Bayesian inference/ probabilistic modeling.
- Computational statistics.
- Markov chain Monte Carlo methods such as Hamiltonian Monte Carlo.
- Programming in Python, R, Mathematica.
- Programming in Stan or similar probabilistic programming frameworks.
- Fourier analysis.
- Mathematical biology.
- Mathematical modelling.
© EuroJobsites 2024
