Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Chalmers University of Technology
- Umeå University
- SciLifeLab
- Linköping University
- Lulea University of Technology
- Swedish University of Agricultural Sciences
- Jönköping University
- Mälardalen University
- Nature Careers
- University of Lund
- Blekinge Institute of Technology
- Linnaeus University
- 2 more »
- « less
-
Field
-
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
-
information about us, please visit: the Department of Biochemistry and Biophysics . About the DDLS PhD student program Data-driven life science (DDLS) uses data, computational methods and artificial
-
engineering challenges. Currently, three postdocs and about 15 PhD students are working within our main research areas: Lightweight materials and structures, multi-phase and metallic materials, Process modeling
-
and career advancement across the globe. DDLS industrial PhD position We are announcing the position of Data-driven life science (DDLS) PhD student in data driven cell and molecular biology. This is an
-
of focus are robotics for mines, construction sites, aerial inspection of aging infrastructure, multi-robotic search and rescue, multi sensorial fusion and multirobot coordination, including multirobot
-
skills and knowledge while contributing to a more sustainable future through tomorrow’s manufacturing technologies. Information about the department The main competences at the Department of Industrial and
-
, the extensive image information requires great accuracy and is therefore time-consuming. Today, detailed image information is collected from MRI and CT systems on a large scale in various cohort studies, often
-
, 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
-
long-term, and most often global, perspectives on future renewable fuels for transport. We seek to rigorously analyse the feasibility of energy transitions, utilize empirical as well as estimated data
-
using state-of-the-art single-cell omics technologies. The team consists of the principal investigator, two experimental scientists (doctoral students), one bioinformatician (postdoc), and one