Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- Linköping University
- Lunds universitet
- University of Lund
- Uppsala universitet
- KTH Royal Institute of Technology
- Karolinska Institutet (KI)
- SciLifeLab
- Lulea University of Technology
- Luleå University of Technology
- Swedish University of Agricultural Sciences
- IFM, Linköping University
- Umeå University
- University of Borås
- University of Gothenburg
- Göteborgs Universitet
- Högskolan Väst
- IFM/Linköping University
- KTH
- Kungliga Tekniska högskolan
- Linnaeus University
- Linneuniversitetet
- Luleå tekniska universitet
- Mid Sweden University
- Mälardalen University
- Nature Careers
- Stockholms universitet
- Umeå universitet stipendiemodul
- Örebro University
- 19 more »
- « less
-
Field
-
optimization and functional characterization of small molecules Integrating biophysical, computational, and cell‑based data Independent experimental design, data analysis, and interpretation Active participation
-
innovative approaches to design and optimize materials with enhanced bioactivity. Experience in design and synthesis of peptides will be considered a strong merit, as well as expertise in chemical modification
-
: - Distributed robotic autonomy for embodied intelligence - Data-driven and learning-based control - Decentralized decision-making and distributed optimization - Belief-space and uncertainty-aware planning - Neuro
-
at the Faculty of Medicine. Clinical Sciences Lund cooperates closely with Skåne University Hospital and the Faculty of Medicine in order to optimize the conditions for preclinical and clinical translational
-
microscopy on magnetic materials and/or the use and development of coherent x-ray microscopy techniques, to join the SoftiMAX team. As part of the team, you will ensure optimal operation of the beamline plus
-
materials, formulating and optimizing electrolyte systems (including hybrid solvents, functional additives, and water-in-salt electrolytes), and investigating the electrochemical performances of designed
-
with FPGA programming used in superconducting quantum circuit experiments. Model-Free Quantum Control via Reinforcement Learning: Reinforcement learning (RL) is an emerging approach for optimizing
-
in clinically relevant environments. Key work assignments include: Design, fabrication, and optimization of high-performance plasmonic nanostructures and SERS substrates for sensing in complex
-
of waste heat, energy efficiency measures, digitalized control and optimization strategies, issues related to security of supply, and how sector‑coupled solutions can enhance flexibility and reduce the
-
competence in image analysis and data processing. What you will do Develop and optimize experimental workflows, including sample preparation under different environmental conditions. Design and conduct