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Advance Fall Risk Prediction and Rehabilitation with Cutting-Edge Sensing Technologies! Are you passionate about research that makes a real difference in people’s lives and society? Do you thrive
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cancer. The goal will be to find genetic prediction models to be able to predict which childhood cancer patients have a high or low risk of toxicity in childhood cancer. Preliminary the doctoral project
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aims to build predictive and physical binding models of protein – DNA interactions using high-throughput and quantitative biochemical binding data across hundreds of thousands of sequence variants
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gene expression profiles and cellular heterogeneity within tissues can predict how existing drugs might act on previously uncharacterized disease mechanisms or cellular subtypes. These models will be
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(education/courses or thesis project) in computational microscale modelling What you will do Develop a finite element analysis framework to accurately predict mechanical properties of recycled aluminium
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This PhD position offers a unique opportunity to advance safe and transparent control for autonomous, over-actuated electric vehicles. You will work at the intersection of model predictive control
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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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mathematical models, validating them with experimental data, and making predictions. The ultimate goal is to decode the mechanisms behind intra-organelle coordination. Besides plant cells, such coordination is a
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, mitochondria, and chloroplasts. The project will involve developing mathematical models, validating them with experimental data, and making predictions. The ultimate goal is to decode the mechanisms behind intra
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. David Marlevi, Prof. Ulf Hedin, and Dr. Ljubica Matic to improve stroke risk prediction for patients with carotid atherosclerosis using a multidisciplinary combination of data-driven imaging