Postdoctoral Fellowship in Glycan-Focused Machine Learning

OPPORTUNITY DETAILS

Total reward

0 $

State University

University of Gothenburg

Area

Central and Eastern Europe

Host Country

Sweden

Deadline

15 Feb 2021

Study level

Doctoral Degree

Opportunity type

Post-doctoral

Specialities

Information technology and computer science , Biology

Opportunity funding

Not funding

Eligible Countries

This opportunity is destined for all countries

Eligible Region

All Regions

The Department of Chemistry and Molecular Biology at the University of Gothenburg is looking for a postdoctoral researcher with computational experience and interest in glycobiology and machine learning.

Project

The Bojar group is located in the Molecular and Cellular Biology Division of the Department of Chemistry and Molecular Biology as well as the Wallenberg Centre for Molecular and Translational Medicine of the University of Gothenburg. We are a rapidly growing and multidisciplinary research group that focuses on the study of glycans and their role in biology using both experimental as well as computational techniques.

Our research focuses on the development and application of novel methods in the areas of glycan-focused machine learning and bioinformatics. Broad areas of interest concern the extraction of functional information from glycan sequences and the prediction of glycan repertoires of biological systems. We further engage in the development and implementation of methods from synthetic biology / genetic engineering to perturb the glycan repertoires of biological systems and assess the performance of glycan biosynthesis under different environmental conditions as well as the impact of glycans on signaling pathways. Insights gained from these endeavors will further our understanding of molecular biology and have broad biomedical implications.

During postdoctoral training, you will design, develop, and apply new algorithms in the broader area of glycan-focused machine learning. Among others, these will be used to generally enhance the predictive capabilities of machine learning or deep learning models applied to glycobiology and lead to more mechanistic insights. Further applications will include various sequence-to-function models illuminating the role of glycans in a range of biological contexts. Communication with more experimentally focused members of the team will be a crucial component of this project. If desired, you will also be able to learn the experimental methods used in the group. We encourage you to gain experience in the co-supervision of Ph.D. students and M.Sc. thesis students and you may also attend international conferences and meetings if possible. You will be directly supervised by Dr. Daniel Bojar and become a part of the Department of Chemistry and Molecular Biology as well as the Wallenberg Centre for Molecular and Translational Medicine of the University of Gothenburg.