Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- Linköping University
- KTH Royal Institute of Technology
- Karolinska Institutet (KI)
- Lulea University of Technology
- Lunds universitet
- SciLifeLab
- Umeå University
- University of Lund
- Luleå tekniska universitet
- Swedish University of Agricultural Sciences
- Mälardalen University
- Umeå universitet stipendiemodul
- Uppsala universitet
- Blekinge Institute of Technology
- Karlstad University
- Luleå University of Technology
- The Swedish University of Agricultural Sciences
- Uppsala University
- Institutionen för biologi och miljövetenskap
- Jönköping University
- Karlstads universitet
- The Royal Institute of Technology (KTH)
- The Swedish University of Agricultural Sciences (SLU)
- 14 more »
- « less
-
Field
-
of Computer Science. The group is led by Associate Professor Emma Söderberg and conducts research at the intersection of software engineering, developer tool construction and human–computer interaction. Ongoing
-
are professors. Our mission is to advance the understanding of forest ecosystems and how these should be managed today and in the future. For more information: http://www.slu.se/en/departments/forest-ecology
-
- to demonstrate scalable verification of quantum bosonic processors towards quantum advantage. (2) Quantum-enabling technologies - to develop traveling wave parametric amplifiers (TWPAs) based on the nonlinear
-
the laboratory and field studies, including the development and pilot testing of experimental designs, measurement methods and study protocols. Conducting visual tests and computer-based tasks under different
-
in computational fluid dynamics Experience in computer programming, in particular Python and Matlab, and in CAD and CAE tools Ability to work independently and also to enjoy collaborating with others
-
. Plant science/ecology, especially related to forest ecosystems. Computer programming. Data analysis (machine learning, statistics, numerical analysis, time-series analysis, etc.). Quantitative methods in
-
Engineering, Computer Engineering, Mechatronics Engineering, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or other related subjects. Experience working on experimental
-
qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
-
analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
-
been completed earlier. Additional requirements: Very good oral and written proficiency in English. Documented proficiency in computer programming. Track record of preparing and publishing high-quality