Sort by
Refine Your Search
-
treatment targets? Would you like to work together with competent and friendly colleagues in an international environment? Are you seeking an employer that offers safe and favorable working conditions? We
-
department’s activities here: https://www.uu.se/en/department/immunology-genetics-and-pathology Read more about our benefits and what it is like to work at Uppsala University The Data-driven life science (DDLS
-
transforms our knowledge about how cells function by peering into their molecular components in time and space, from single molecules to native tissue environments. The project aims to design data-driven
-
Are you passionate about applying computational approaches to solve problems in biomedicine? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a cutting-edge
-
, prevention and treatment? Work duties The main duties of the doctoral student are to conduct their own research education. Duties include: i) Data science focusing on analytical pipelines to address
-
you like to work together with competent and friendly colleagues in an international environment? Are you seeking an employer that offers safe and favorable working conditions? We welcome you to apply
-
requirement for English equivalent to English B/6. Selection In order to succeed as a doctoral student at KTH you need to be goal oriented and persevering in your work. During the selection process, candidates
-
at the single-cell level, using tools from optimal transport, mathematical optimization, and machine learning. In addition to method development, the work includes applying and benchmarking algorithms on both
-
of elective courses and the opportunity to work in a leading research group. Karolinska Institutet collaborates with prominent universities from all around the world, which ensures opportunities
-
. The student will work in a group addressing all these challenges, developing new AI-based methods to improve biological realism in simulations which will lead to more accurately inferred GRNs from real data