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computing. This particular position focuses on time-series analysis and forecasting using transformer based foundation models. About the Project Time-series prediction using transformer based models is
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applications for a unique postdoctoral position focused on the development of digital models of the human colon and surrounding organs to simulate their behaviour during colonoscopy procedures. The successful
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probes and in combination. More specifically, the project requires developing the SBI framework including simulations as forward models of observables, performing inference on synthetic datasets and
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performance. To validate the achieved tuning range and functional performance in laboratory measurements against modeling and simulation results. This position is part of the MetaTune Doctoral Network
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learning workflows, and developing complete models. Example applications include drug design, cryo-electron microscopy, structural prediction and dynamic simulation of biological macromolecules, genomics
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to mechanical stimulation Methods and Approaches: The project combines state-of-the-art experimental and computational techniques, including: Transgenic mouse models and lineage tracing Orthodontic tooth movement
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models, performance evaluation criteria, and the grant contract model are those approved under the University of Coimbra's Research Grant Regulations. Where to apply Website https://www.apply.uc.pt
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data, model-based simulation coupling, and uncertainty-aware outputs for lab/clinical validation. Work with 3D datasets, time-series sensors, and multi-omics or assay data to create predictive models and
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build upon the existing Alpha framework (originally developed to model protein quality, see https://alpha-tool.eu ) and further develop it as a research-oriented modelling and demonstration platform
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improved care for people affected by prostate cancer (PCa) or kidney cancer (KC). This position will focus on modeling AI trustworthiness and explainability in medical data and models (mainly imaging data