34 phd-mathematical-modelling-population-modelling Postdoctoral research jobs at Chalmers University of Technology
Sort by
Refine Your Search
-
to benchmark results, validate models against fabricated amplifier designs, and - very importantly - guide technology development Publish results in leading journals and conferences, and supervise PhD students
-
Join us to pioneer next-generation generative models that accelerate molecular dynamics. We seek a postdoctoral researcher to develop AI surrogates for molecular dynamics (MD), slashing
-
University of Technology , where you will develop explainable AI models for personalized treatment planning in sports medicine and orthopaedics. You will work in a highly interdisciplinary environment
-
explainable AI models for personalized treatment planning in sports medicine and orthopaedics. You will work in a highly interdisciplinary environment, collaborating with leading experts in AI, mathematics
-
applying methods from quantum field theory, computational physics, statistics, and applied mathematics. Within astroparticle physics, our focus spans from the theoretical modeling of systems and phenomena
-
The Division of Vehicle Safety studies accidents, driver reactions, and injury mechanisms. The Injury Prevention group develops Human Body Models to predict injuries for the whole population, in collaboration
-
Are you passionate about pushing the boundaries of medical research? Join us at Chalmers University of Technology to explore how advanced models can transform the way we study treatments. We
-
formulations as complementary model systems. Integrate experimental work with spin-diffusion modeling and other complementary techniques. Collaborate actively with AstraZeneca (model systems and analytical input
-
for self-deployable 6G networks in the edge continuum (EC-DEPLOY-6G) pioneers the use of large language model–driven agents to autonomously configure and deploy 6G and cloud functions. The project leverages
-
. The postdoc will systematically model adversarial capabilities, develop proactive mitigation strategies, and evaluate their effectiveness in large-scale experimental settings. Who we are looking