40 computational-model PhD scholarships at Technical University of Denmark in Denmark
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modelling approaches will also be used to complement the experimental work. The bioprocess engineering team at DTU Chemical Engineering consists of around 10 scientists and engineers. Expertise is available
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privacy guarantees. This PhD project will develop scalable, privacy-preserving coordination models that jointly optimize DER integration, electrified loads, and data-center flexibility — ensuring fairness
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benefits and a structured PhD training program About the research group You will join the Biomimetics, Biocarriers and Bioimplants group (The 3Bs), led by Associate Professor Leticia Hosta-Rigau at DTU
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modelling, and prediction tools. Fouling Control Coatings Fouling Control is performed by specifically designed materials to remove or prevent biofouling from i.e. ship hulls, as bio fouling leads
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primarily experimental, complemented by numerical modeling, and will be carried out within the “Fiber Optics, Devices, and Nonlinear Effects” group at DTU Electro. As a PhD student, you will be part of a
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science applications Computational Atomic-scale Materials Design with a focus on materials modeling and discovery with electronic structure calculations and machine learning Luminescence Physics and
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candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU's rules
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vitro and in vivo models of immunology Experience with mRNA-based vaccines and adjuvant formulation Capable of handling a multifaceted project with many stakeholders and collaborators You are expected
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monitoring Statistical analysis and modelling of relevant data (e.g. environmental data). Publishing results in peer-reviewed scientific journals. Fisheries management and conservation (e.g. biodiversity
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). Responsibilities and qualifications As part of the DECIDE project you will be working on developing next generation of tools for decision making under uncertainty. You must: Have experience in AI models (e.g