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Field
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as ProteinMPNN, RFdiffusion, and AlphaFold; prior hands-on use is beneficial but not required. Analytical chemistry: Experience or willingness to learn LC–MS, NMR, and UV–Vis for product and protein
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analysis and analytical data analysis workflows, together with other team members Implementing AI-based microscopy image analysis software as python packages Developing algorithms to deploy machine learning
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modelling, multi-disciplinary optimization or AI-based surrogate modelling techniques. · Soft skills: o Strong analytical and problem-solving abilities. o Excellent communication and technical
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
behavior and provides active personalized learning for improved instant decision making. Key beneficiaries are expected to be construction industry stakeholders, for example, project owners, architects
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We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of
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Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter identification and machine learning. The key challenge is striking a balance between, on
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to this position: A Master's degree in Social Psychology, Work & Organizational Psychology, Management, or a related field. Quantitative research and data analytic skills; Qualitative data analysis skills are a pre
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution
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into the enzyme-substrate interaction in the same set of enzymes. Further, there will be collaboration with a PhD student from NTNU working with similar analytical methods on another class of carbohydrate-active
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to incorporate additional field data. This PhD project offers a great opportunity to work with large-scale biodiversity and climate datasets, develop strong analytical skills, and collaborate with international