Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Umeå University
- Lunds universitet
- Karolinska Institutet (KI)
- SciLifeLab
- Swedish University of Agricultural Sciences
- Linköping University
- University of Lund
- Umeå universitet stipendiemodul
- Blekinge Institute of Technology
- Lulea University of Technology
- Luleå tekniska universitet
- Mälardalen University
- The Swedish University of Agricultural Sciences
- Karlstad University
- Luleå University of Technology
- Umeå universitet
- Institutionen för biologi och miljövetenskap
- Jönköping University
- Linköping University (LiU)
- Sveriges Lantbruksuniversitet
- The Royal Institute of Technology (KTH)
- University of Borås
- University of Skövde
- Uppsala University
- Uppsala universitet
- universitypositions
- 18 more »
- « less
-
Field
-
estimators such as Design-based Supervised Learning and Prediction-Powered Inference, and applying mechanistic interpretability techniques, for example sparse feature circuits and the SHIFT method, so that
-
regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
-
design software such as MATLAB/Simulink, LabVIEW or similar software are required. Experience working on quality monitoring of food and/or agriculture products is highly desirable. Experience in electronic
-
, automation, autonomous systems and industrial digitalisation. Links: Geometry Assurance & Robust Design: https://www.chalmers.se/en/departments/me/research/product-development/geometry-assurance-robust-design
-
and Technical Acoustics is looking for a postdoc for the Swedish Research Council-funded SMILE project (Soundscape engineering with Metamaterial Innovation and LEarning). SMILE develops acoustic design
-
/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized by advanced autonomy for improving the ability
-
program, including complementary intelligence, open-endedness, and the intersection of AI with for example video games, design, creativity, and philosophy. Who we are looking for The following requirements
-
regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
-
), statistical analysis of LHC data or beyond-the-Standard-Model phenomenology, is meriting. Experience with large-scale training on GPU and HPC systems, with design of experiments and active learning, with open
-
. About us The Department of Life Sciences is aiming at bridging cutting edge life science research with biochemical engineering, in order to emerge as the leading innovation center in the region