Sort by
Refine Your Search
-
Category
-
Employer
- Umeå University
- Uppsala universitet
- Linköpings universitet
- Luleå University of Technology
- SciLifeLab
- Umeå universitet
- Chalmers University of Technology
- Linkopings universitet
- Linköping University
- Lulea University of Technology
- Lunds universitet
- Swedish University of Agricultural Sciences
- University of Lund
- 3 more »
- « less
-
Field
-
, machine learning or similar. Alternatively, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms
-
, signal processing and/or wireless communication. Basic knowledge of and/or experience in working with reinforcement learning/other machine learning algorithms Excellent command of spoken and written
-
the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
-
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Our research group studies the ecological and evolutionary drivers of floral
-
, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems. Project description This PhD project is linked
-
absorption/fluorescence and scattering experiments at X-ray free electron lasers. Your focus will be to derive new algorithms for interpretation of the scattering data by introducing chemical force-fields via
-
questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
-
provides a unique opportunity to work at the intersection of AI and experimental science, combining fundamental algorithmic development with real-world applications in scientific imaging. Due to limitations
-
questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
-
divisome protein complexes. Prokaryotic cytoskeleton proteins offer a fantastic and unexplored world of protein polymer assemblies with diverse similarities and evolutionary aspects comparable