Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Linköping University
- Uppsala universitet
- Umeå University
- Linköpings universitet
- Umeå universitet
- Lunds universitet
- Mälardalen University
- Swedish University of Agricultural Sciences
- University of Lund
- Chalmers University of Technology
- Institutionen för biomedicinsk vetenskap
- KTH Royal Institute of Technology
- Linkopings universitet
- Luleå University of Technology
- School of Business, Society and Engineering
- SciLifeLab
- Stockholms universitet
- 7 more »
- « less
-
Field
-
multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
-
to assimilate knowledge at the research level. Understanding and experience in machine learning and computer vision. Knowledge, experience, and strong interest and in AI and XR development. Knowledge and
-
analyses and machine learning. Some data for the project already exist, but additional data will be collected from behavioural tests on privately owned pet dogs in Sweden and abroad (Europe). Travel and time
-
computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as
-
capabilities of nonlinear quantum systems, employing tools from quantum information theory and quantum metrology. The work will involve learning and applying mathematical methods to solve open quantum dynamics
-
interdisciplinary, applied research with expertise in visualization, design, computer graphics, and the learning sciences. The research nexus for the division is the Visualization Center C, a unique science center in
-
approaches that combine artificial intelligence, machine learning, natural language processing, and social sciences. This collaborative and cross-sectoral approach aims to produce robust methods for evaluating
-
quantified, and machine learning will be used. Duties As a PhD student, you will work toward a doctoral degree as the final goal, according to the goals specified in the Higher Education Ordinance. In parallel
-
/thesis: Challenges and opportunities with remote sensing and machine learning in forestry Research subject : Soil science Description: WIFORCE Research School Do you want to contribute to the future
-
and documented background in machine learning, deep learning, data analysis and programming. Previous experience in research and knowledge in bioinformatics, biophysics, biochemistry, molecular biology