20 phd-energy-or-power-or-grid-or-optimization Postdoctoral research jobs at Chalmers University of Technology
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-14158 Is the Job related to staff position within a Research Infrastructure? No Offer Description We are looking for a Postdoc to become part of our team at the Division of Subatomic, High-Energy and
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We are looking for a Postdoc to become part of our team at the Division of Subatomic, High-Energy and Plasma Physics at the Department of Physics. Join our innovative team and contribute to exciting
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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collaboration with the Multiscale Inorganic Materials group, both part of the Division of Energy and Materials at Chalmers . The two groups together comprise nine senior researchers and 27 PhD students and
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energy use and minimizing environmental impact. This collaborative effort brings together expertise in materials science, physics, polymer chemistry, and composite mechanics, with a particular emphasis on
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possess a problem-solving analytical ability. You are willing to help with the supervision of PhD and Master’s students What we offer Chalmers provides a cultivating and inspiring working environment in
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models into Chalmers’ bridge simulators in collaboration with other researchers. You are also expected to supervise PhD and MSc students and to publish at least two peer-reviewed journal articles during
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through publications in high-impact journals and presentations at international conferences. Qualifications A PhD in Physics, Chemistry, Mechanical Engineering, Energy Sciences, or a related field, obtained
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Parkinson. We use in vitro biophysical analysis to characterise protein aggregates and their formation in combination with advanced live cell fluorescence imaging and cell model development to study protein