41 software-formal-method-phd Postdoctoral positions at Chalmers University of Technology
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                tested in high hydrogen pressure reactors and the gas will be analysed with GC. A central part of the work will be detailed catalyst characterization. A wide range of methods will be used, including XRD 
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                Demonstrated experience with LS-DYNA or comparable commercial FEA software Proficiency in Python programming for scientific computing and machine learning applications Experience with machine learning methods 
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                properties. Advanced characterization methods and development of new techniques – We specialize in hyphenated rheological methods such as rheo-SAXS and rheo-DES, which are primarily applied to materials like 
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                pharmaceutical materials. In this postdoctoral project, chemically modified cellulose fibers and pharmaceutical formulations are the focus. The aim is to adapt and develop methods in solid-state DNP-NMR 
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                (AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines 
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                own research in a research group. The position may also include teaching on undergraduate and master's levels as well as supervising master's and/or PhD students to a certain extent. Another important 
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                materials to direct industrial projects generating new inventions. We have a strong learning commitment on all levels from undergraduate to PhD studies where physics meet engineering. The research 
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                on two main lines of research. The first concerns the modeling of general dark matter–electron interactions in detector materials. This will be achieved by combining methods from particle and solid state 
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                to contribute your own research ideas and take part in supervising PhD students. About the research project The position, starting in the first half of 2026, will be based in the theory division of the Department 
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                collaboration with others, and to coach PhD students. You will be expected to develop your skills, the team, and contribute with your creative ideas. We value a collaborative attitude and an interest in working