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/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a
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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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models, patient material, and cutting-edge technologies to study how the immune system can be harnessed to develop cancer immunotherapies. In particular, we are studying how oncolytic virotherapy can be
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! The research group The PhD student will be based both at AstraZeneca, Gothenburg, and at Chalmers University of Technology. At Chalmers, the student will be a part of the Holme Lab, based
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based on the Arctic region, we create global social benefit. Our scientific and artistic research and education are conducted in close collaboration with international, national and regional companies
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molecular mechanisms that drive its invasive behavior, both general and patient-specific. Using cutting-edge spatial techniques and CRISPR-based methods, we build data-driven models that link gene regulation
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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materials for synthesizing different types of hydrogen storage molecules. Using advanced quantum mechanical calculations, you will develop multi-scale models to study reaction kinetics and improve catalyst
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well as cell- based model studies and apply advanced data-driven approaches and state of the art biochemical and OMICs technologies to understand and predict the role of foods, dietary components and dietary
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based integration of software-defined CPS (Cyber-Physical Systems) and IoT devices. -Replication and software updates during runtime for mission-critical devices and systems. -Model based engineering