Sort by
Refine Your Search
-
in large pre-trained models (vision-language models), generative models (flow matching, diffusion), simulation-based inference, and robust and active learning. The group has a wide network of
-
. Simulation-based inference (SBI) addresses this by training neural networks, such as flow-matching generative models, on simulated events. The project aims to develop efficient, robust and calibrated SBI
-
and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
-
and directing students achieve individual and collective research goals. This provides opportunities for training in scientific leadership for eventual application as an independent group leader
-
KTH Royal Institute of Technology, School of Engineering Sciences Job description The AICell Lab (https://aicell.io ) in the department of Applied Physics at KTH and Science for Life Laboratory is a
-
are also included as important aspects of the employment. You will also have the possibility to contribute to applications for external research funds. In this project, your responsibilities will include