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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
multi-physics modelling of electrochemical processes can be a plus. We value candidates who are collaborative team players, intellectually curious, and open to exploring new research directions. A track
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
proficiency in Python is required, and hands-on experience with ML libraries such as PyTorch is expected. Theoretical understanding and experience with multi-physics modelling of electrochemical processes can
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degradation. The candidate is expected to have a strong background in biotechnology, enabling them to design new valorization strategies and process scale-up. The position will be filled for a fixed-term period
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well as to prepare new devices and methods of quantum information processing. Our goal is to achieve JoFETs by utilizing hybrid devices based on silicon and high-quality superconducting silicides. Remarkably
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in topological materials and eagerness to work on tough experimental challenges. We expect the candidates to have: PhD degree in physics or in a nearby field Experience on 2D materials and quantum
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. The position gives excellent opportunities in publishing in high-quality forums. We expect the applicants to have a PhD degree (or close to completing one) in computer science, mathematics or statistics, with
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data, including biomedicine and drug discovery. The position gives excellent opportunities in publishing in high-quality forums. We expect the applicants to have a PhD degree (or close to completing one
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(Department of Mechanical Engineering) educates game-changing energy and HVAC engineers and researchers, supports industries and communities in their decarbonization and green energy transition processes and
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Applications (EMA) research group (https://www.aalto.fi/en/department-of-chemistry-and-materials-science/electrochemical-materials-and-applications ), led by Prof. Daniel Martin-Yerga, is seeking a highly
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methods of quantum information processing. Our goal is to achieve JoFETs by utilizing hybrid devices based on silicon and high-quality superconducting silicides. Remarkably, silicides hold promise