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Develop soft, 3D-printed hydrogel bioelectronics for next-generation neural interfaces. Job description A 4-year PhD candidate position is available in the research group of Achilleas Savva in
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Are you interested in using data science to understand how digital measures can capture clinically meaningful aspects of reward, motivation and impulsivity? Do you want to develop and apply
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produce data that looks plausible but violates physics and is therefore of limited use for grid planning. As a PhD candidate you will develop physics-informed, domain-constrained generative models
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, which will use the digital twin together with monitoring data to develop prognostic structural health monitoring strategies. In this project you will: Perform experimental characterization of the static
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; expand academic, professional and personal skills; use high-end compute infrastructure via the national ICT cooperative (SURF) What we ask of you You are passionate about research and want to develop
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’ preferences in terms of ‘productive agriculture’ and ‘healthy biodiversity’ into quantifiable impact indicators; Develop a spatial optimization algorithm that finds land use configurations that optimize
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used to model leukodystrophies because of their genetic tractability and the ability to study early brain development. To strengthen their use as preclinical models, this project will develop outcome
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Fixed-term contract: 12 months. What do we offer? We offer a dynamic and inspiring environment with excellent support for experimental work and analysis, and great opportunities for collaboration
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are seeking a PhD candidate for a 4-year contract to develop and apply computational models and video-based tools to capture hand movement and function with deployment in the home environment as the target
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how these decisions are currently made in practice, and how uncertainty could be managed in the future. You will explore how uncertainty in clinical evidence is described and assessed, which factors