Sort by
Refine Your Search
-
-research-school/ . The future of life science is data-driven. Will you be part of that change? Then join us in this unique program! Project description At the Department of Biochemistry and Biophysics
-
year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
-
, computer science, computational biology and computational statistics. More information about us, please visit: Department of Mathematics . Project description We seek to recruit a PhD student for the following
-
university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Biology-informed Robust AI Methods for Inferring Complex Gene Regulatory
-
studies on carotid atherosclerosis, offering unprecedented opportunities for both scientific and clinical impact. The project setting and DDLS Research School Data-driven life science (DDLS) uses data
-
The doctoral student project and the duties of the doctoral student This Data Driven Life Sciences (DDLS) PhD project focuses on probabilistic models of protein structure, which can be used primarily
-
The section of Radiology at the Department of Surgical Sciences, Uppsala University, is organized in several research groups that conduct research within the development and application of imaging
-
: the Department of Biochemistry and Biophysics . Project description The Drug Discovery and Development Platform at Science for Life Laboratory (SciLifeLab DDD) is a national infrastructure for academic
-
epidemiology and biology of infection. The expected starting date is September 2025, or as otherwise agreed. Project description This PhD project is part of the Data-Driven Life Science (DDLS) research school
-
KTH Royal Institute of Technology, School of Electrical Engineering and Computer Science Project description Third-cycle subject: Computer Science This project involves generative modeling