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Field
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focus lies on nucleic-acid delivery for next-generation therapeutics. This PhD project aims to develop lipid-based nanoparticles for the controlled co-delivery of multiple genetic cargos to cancer cells
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not necessary as training will be provided. Experience of computer modelling is desirable but not essential as full training will be provided in an active and well-resourced research group based in
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Expert Panel members. Based on these findings, you will develop realistic case scenarios that present different types and levels of uncertainty. These scenarios will be discussed with patients, clinicians
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calibration, uncertainty quantification and machine-learning-based surrogate modelling have been developed for nuclear fuel-performance simulations. You will further develop these methods to enable faster and
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and treatment of adrenal diseases. Digital medicine is entering a new era where human “digital twins” and sensor-based monitoring allow personalised diagnosis and treatment. ENDOTRAIN will train a new
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help unlock the data needed for the energy transition? In the NWO-funded SHARE project, you will develop AI models that generate realistic, privacy-preserving synthetic energy data for grid planning and
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, quantitative image analysis, data processing and machine-learning-based modelling. More about the position The main purpose of the fellowship is research training leading to the successful completion of a PhD
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‑violation. For example, the candidate will do some of the tasks including: AI-driven Link Adaptation and MAC control – develop AI-based mechanism that proactively anticipate and respond to rapidly changing
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also interview professionals involved in the assessment of medical devices, such as notified-body assessors, regulators, and Expert Panel members. Based on these findings, you will develop realistic case
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a nuclear reactor on a ship presents a fundamentally different challenge from controlling a land-based plant. A shipboard reactor must respond to a continuously varying electrical and propulsion load