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Experience in machine learning for neural data What you will do Take courses at an advanced level within the Graduate school of Electrical Engineering ( Graduate schools | Chalmers ) Develop your own
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application! Your work assignments Spatio-temporal processes are everywhere in science and engineering, with applications ranging from weather prediction to cardiovascular medicine. Developing machine learning
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algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics, spanning diverse application domains such as medicine, energy systems, biomedical
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, enzymology, or molecular biology - Experience with computational methods (e.g. de novo protein design, molecular modelling, machine learning, or bioinformatics) - Experience with biochemical or biophysical
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now teach courses in several engineering programmes at bachelor’s and master’s levels, as well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se
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areas (demonstrated through peer-reviewed articles or pre-prints): Applied Machine Learning (ML) for industrial settings like part-autonomous robots, and building simulation or test environments
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‑mining and machine‑learning methods. The expected scientific outcome is to establish guidelines for identifying and optimizing promising electrolyte materials and to support the development of future
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biology platform https://www.scilifelab.se/units/structural-proteomics/ The unit provides access to cutting-edge equipment and expertise, for the analysis of protein interactions and conformational dynamics
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Do you want to learn how to do machine learning on a real quantum computer, with application to real problems from Life Science? About us The Wallenberg Centre for Quantum Technology (WACQT ) is a
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. The work will primarily entail design, implementation, and evaluation of distributed systems and networks for machine learning inference. Applying machine learning concepts, with the goal of devising agentic