Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Uppsala universitet
- Sveriges lantbruksuniversitet
- Umeå University
- Chalmers University of Technology
- Mälardalen University
- SciLifeLab
- Swedish University of Agricultural Sciences
- Chalmers University of Techonology
- Chalmers tekniska högskola
- Fureho AB
- Institutionen för biomedicinsk vetenskap
- Karolinska Institutet, doctoral positions
- Linköping University
- Luleå University of Technology
- Lunds universitet
- Mälardalens universitet
- Nature Careers
- Stockholms universitet
- Umeå universitet
- University of Gothenburg
- 10 more »
- « less
-
Field
-
modeling molecular dynamics using our trapped Rydberg ion technology. This position is part of the ERC Synergy project "Open 2D Quantum Simulator (OPEN-2QS)", which start on 1 May 2025. The OPEN-2QS project
-
directly relevant to the specific specialization. It is a requirement that you have: Experience working with Agent-based Modeling and Simulation Experience working with Agent-based Modeling and Simulation
-
of Electrical Engineering. Project description: Autonomous vehicles for mining and mobile robotics for industrial processes require complex motion planning as well as safe model-based predictive control and
-
) position in Medical Cell Biology – Development of Advanced Tissue Models Admission to Doctoral (PhD) Studies in the subject of Medical Cell Biology Dept. of Medical Cell Biology, Disciplinary Domain
-
at cell membranes; Apply machine-learning models trained on simulation data to study how lipid composition and genetic variation influence the conformational and phase properties of membrane-associated
-
scenarios. Duties Your work will focus on modeling and optimizing hydrogen compression, storage, and fueling processes at the system level. This includes, among other tasks: Thermodynamic simulations of CGH
-
. Excellent command of spoken and written English. Additional qualifications Experience with modelling, simulation, and optimization of energy systems. Experience in thermodynamic analysis, particularly
-
statistical and algorithmic methods to analyze large amounts of simulation data, models that explain how and why an autonomously controlled machine fails or underperforms, and methods to recognize simulation
-
statistical and algorithmic methods to analyze large amounts of simulation data, models that explain how and why an autonomously controlled machine fails or underperforms, and methods to recognize simulation
-
experimental approaches, with theoretical activities focusing on: Quantum mechanical calculations using density functional theory. Mean-field modeling and Monte Carlo simulations for reaction kinetics