30 software-formal-method-phd research jobs at Chalmers University of Technology in Sweden
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fundamental questions about the particles and forces governing our Universe to energy-related research. The methods of our investigations are also diverse and complementary, and range from theory and computer
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the work will be detailed catalyst characterization. A wide range of methods will be used, including XRD, BET, SEM, TEM, TPR, TPD, DRIFT, and XPS. Atom Probe Tomography (APT), with sample preparation
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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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research. The methods of our investigations are also diverse and complementary, and range from theory and computer simulations to experiments in subatomic physics. The Plasma Theory group within the Division
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)* Strong background in computational mechanics and numerical methods Demonstrated experience with LS-DYNA or comparable commercial FEA software Proficiency in Python programming for scientific computing and
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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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involve established software tools, such as: CHEMKIN-PRO for steady one-dimensional simulations of laminar flames with detailed chemistry. CONVERGE for unsteady three-dimensional simulations of turbulent
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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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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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(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