96 algorithm-development PhD scholarships at Technical University of Denmark in Denmark
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description Machine learning opens up new opportunities to accelerate the discovery of next-generation energy materials by combining predictive and generative approaches. In this project, we will develop neural
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industrial processes. Your research will drive a paradigm shift in how TES systems are modelled, integrated, and controlled within industrial settings. You will develop novel, adaptive, physics-informed models
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Rodrigues, Prof. Kira Vrist Rønn (SDU), and Associate Prof. Line Harder Clemmensen (KU). You will work on research focused on developing AI-enhanced Agent-based Simulation tools to support Intelligence
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weathering and erosion to sediment transport and landscape evolution. Depending on your background and expertise, your research will focus on one or more of the following areas: Confocal microscopy of point
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of enzyme activity, stability, kinetics, and structure–function relationships. The goal is to gain fundamental insights into enzymatic degradation — knowledge that can ultimately guide the development of more
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for the development of next-generation CAR T cell therapy for solid tumours. You will work with a wide range of methods, including molecular biology, culture of human T cells, CRISPR multiplexed genome engineering
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to join our team. The project will focus on developing innovative silicone-based foams tailored for healthcare applications. Responsibilities and qualifications The project focuses on the design
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communities to cascading hazards, particularly NaTech (Natural Hazard Trig-gering Technological) events. REUNATECH is a Horizon Europe Marie Skłodowska-Curie Doctoral Network that aims to educate and train the
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chromatography, size exclusion chromatography). Familiarity with enzyme kinetics and assay development. Exposure to computational tools like RFdiffusion, ProteinMPNN, or AlphaFold3. Interest in automation and high
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SQL databases and file repositories. We are now taking the next strategic step: developing ontologies and a dynamic knowledge graph to semantically link our internal data systems - and connect them