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23 Oct 2025 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Computer science » Computer architecture Computer science » Other Environmental science » Earth
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machine learning with applications in science. The aim is to develop novel machine learning and other data driven AI methods for scaling up and improving scientific processes beyond what humans can do, for
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focus 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
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allows us to connect 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
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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 simulations
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, exact and approximate inference, and neurosymbolics. See Martin Trapp’s website for details. The candidate is expected to augment the research expertise of the group through her/his own experience and to
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control technology and computer algorithms to develop a foundational discovery platform for future cell programming applications. This position involves both experimental and computational work
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well as nuclear physics. This diversity of research topics allows us to connect fundamental questions about the particles and forces governing our Universe to energy-related research. The methods of our
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no more than three years prior to the application deadline*. A working knowledge of advanced methods in High-Energy physics, in particular quantum field theory and particle physics is required. Familiarity with
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is to combine multi-gene control technology and computer algorithms to develop a foundational discovery platform for future cell programming applications. This position involves both experimental and