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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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persist or disappear is often unclear as existing methods to predict contemporary evolution work poorly when applied to natural populations. Recent research suggests that environmental variability is an
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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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’ environments, raising concerns about their ability to evolve fast enough to avoid extinction. Whether species will persist or disappear is often unclear as existing methods to predict contemporary evolution work
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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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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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bioinformatic methods to detect environmental adaptation. The methods will be tested using simulations of genomic data. The work consists of working in Uppsala University’s computer cluster as well as programming
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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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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