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Join us in developing next-generation, machine-learning accelerated computational models to understand and predict coupled ionic and electronic transport in organic materials for sustainable energy
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at the Computational Chemistry and Biochemistry Group (CCBG). The researcher will be tasked with development of a multitasked machine learning (MTL) framework for enzyme design. The work will also include improvement
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next-generation nuclear reactors. Combining expertise in reactor physics, thermal-hydraulics, nuclear safeguards, diagnostic techniques and machine learning applied to nuclear technology, the group
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, and machine-learning approaches to investigate the interplay between atomic structure, dynamics, and electronic properties. We offer an international and collaborative research environment, close
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cabinets and installations. Measurement equipment such as oscilloscopes, multimeters and signal generators. Mechanical workshop skills, such as using a milling machine, drill press and other common workshop
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interpreting results, and benchmarking brain-inspired architectures against conventional machine learning methods. You are also expected to actively participate in academic discussions with supervisors at KTH
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is BTH's largest department, with just over 70 employees. The department conducts research in computer science, covering the subfields of big data and AI, parallel computer systems, visual and
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advanced analytical approaches, including statistical modelling, machine learning, and/or genetic epidemiological methods, to study disease trajectories, risk factors, treatment patterns, and sources
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- Testing and Assurance of Machine Learning and Generative AI Components - robustness and reliability testing, explainability and transparency evaluation, and techniques for detecting data or model drift
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architecture, parallel systems, programming language theory, embedded systems or software engineering. Documented ability to teach operating systems and compiler construction. Practical experience of systems