47 algorithm-development-"Multiple"-"Prof"-"Prof"-"UCL" positions at Chalmers University of Technology in Sweden
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project focuses on developing and refining advanced organ-on-chip technologies to study and optimize nanoparticle-based delivery systems in biologically relevant environments. The project is strongly
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of AI and materials science, addressing real-world challenges in thermal management for high-performance computing and 6G infrastructure. We offer: (1) You will develop marketable skills in AI, ML, and
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We are looking for a postdoc to join a project on carbon capture and utilization (CCU) at Chalmers. In this role, you will focus on developing catalysts and carrying out detailed characterization
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to the development of advanced methods for electrode fabrication, with a particular emphasis on electrophoretic deposition. You will also conduct electrochemical testing under applied magnetic fields to improve
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this role, you will focus on developing catalysts and carrying out detailed characterization experiments that can support the future production of electrofuels and electrochemicals. You will be part of a
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of surface sites makes theoretical understanding difficult. This project will develop and benchmark machine learning models to predict local electronic density of states (DOS) at alloy catalytic sites
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industry, academia, and government agencies. Our mission is to promote and integrate the life cycle perspective into all decision-making processes. We enable skills development and knowledge sharing among
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-making processes. We enable skills development and knowledge sharing among our partners and host a unique network of companies, academia, research institutes, and public authorities. By fostering
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research position. The project assistant will apply their biomedical and AI knowledge to conduct a feasibility study developing AI tools to predict properties of lipid formulations for drug delivery
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with GKN Aerospace Sweden with partial work there and combines numerical and experimental research. Project overview The purpose of this project is to contribute to the development of an ultra-efficient