15 density-functional-theory-molecular-dynamics PhD positions at Chalmers University of Technology
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fluid dynamics and aerodynamics. Ability and motivation to work in a fluid dynamics laboratory environment. Good proficiency in spoken and written English. Meritorious qualifications Relevant coursework
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This PhD position offers a unique opportunity to advance safe and transparent control for autonomous, over-actuated electric vehicles. You will work at the intersection of model predictive control
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of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
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for reactive synthesis. This allows us to describe dynamic behaviors in complex environments over time. You will work with formal tools such as: Planning domains and temporal logic — to describe the required
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This PhD position at Chalmers University of Technology offers an exciting opportunity to work in an interdisciplinary environment and receive training and support in materials design and synthesis
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in a dynamic and international atmosphere. We value diversity and welcome applicants from all backgrounds and identities. The Department of Electrical Engineering The division is part of the Department
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We invite applicants to join our team of researchers within the area of maritime environmental science. We are looking for a PhD student to work on cumulative risk assessment of shipping pressures
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environment. This is an opportunity to combine field work and desktop analyses to advance the understanding of how shipping impacts the marine environment. The research will inform competent authorities on how
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overview The aim of the project is to explore the interplay between the electrical and mechanical properties of conjugated polymers and conducting polymer fibers. A central part of the research will involve
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introduces new and underexplored vulnerabilities to network-based threats. The goal of this research is to uncover such threats, evaluate their impact on training performance and model integrity, and develop