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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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aspects of cheminformatics. The position is founded by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases ”, led by Prof
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
the furthermore, core works are envisioned in (c) initiating novel VLE design using foundational Digital Twin for Construction Safey (DTCS) components (e.g., city models, nD BIM, IoT/sensor data, TPTC, LPS, LBS
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Job Description Are you driven by the potential of AI in enzyme engineering? Do you want to design novel enzymes from scratch using cutting-edge generative models and validate their function in
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are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape response to climate change. Engineering and applied physics
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market frameworks and business models for fair value distribution will be analysed. Responsibilities and qualifications Your primary research tasks will include: Develop and simulate coordinated control
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domains. The scientific outcomes are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape response to climate
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the carbon footprint of milk production. The project will apply advanced statistical methods, artificial intelligence, and cutting-edge genetic models to support and enhance management and breeding decision
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with the aim of making it a practical computational tool in the near term. The project will focus on Gaussian Boson Sampling (GBS), which is a specialized photonic quantum computing model with
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conversion reactions. The second position is focused on modelling stability of electrocatalyst materials. The aim is to develop a framework to predict metastability of catalyst materials. Among the methods