Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Uppsala universitet
- Linköping University
- Linköpings universitet
- Lunds universitet
- Stockholms universitet
- Umeå University
- Chalmers University of Technology
- Umeå universitet
- Mälardalen University
- SciLifeLab
- University of Lund
- Jönköping University
- KTH Royal Institute of Technology
- Luleå University of Technology
- Mälardalens universitet
- School of Business, Society and Engineering
- Sveriges lantbruksuniversitet
- 7 more »
- « less
-
Field
-
, you have gained essentially corresponding knowledge in another way. The applicant is expected to have good knowledge of computer science, mathematics, algorithms, and programming. Knowledge and
-
to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
-
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
-
Technology Laboratory (QTL) division of the Microtechnology and Nanoscience (MC2) department, working in a large team of PhDs, postdocs and researchers. About the research We are seeking PhD students to work
-
, 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
-
fast-paced research environment, a structured and organized approach is highly valued. You will work in a team of researchers from diverse backgrounds, including PhD students and postdocs, and should
-
noble-metal tellurides. The researcher will work together with PhD students, postdocs, and a research engineer, to perform the experiments. Description of the work duties: to perform synthesis
-
questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
-
questions include automated modeling and model simplification/refinement supported by generative AI, system identification, and 3D reconstruction algorithms. Additionally, the research involves developing
-
areas: 1) Public health problems 2) Incentives and organization within healthcare 3) Design of healthcare systems in terms of efficiency and distribution 4) Economic evaluations of health interventions