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an approachable and highly experienced research team. You will explore cutting-edge topics in specification-driven development, large language models, and AI-assisted software engineering. Your job As a PhD
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simulations and thermal comfort analyses by developing fast parametric algorithms and data-driven surrogate modelling approaches capable of predicting dynamic outdoor thermal comfort with high accuracy
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leader in developing, testing, and implementing Collaborative Care, an integrated care model increasingly seen as a solution for population-based mental health care. Other areas of excellence include
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, Computational Linguistics, Machine learning, Computer Engineering or related fields Preferred Qualifications: ● Strong experience implementing and training deep learning models in PyTorch, with attention
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and explainable AI models for Medical Imaging and aid Medical Diagnosis, Digital Health and Well-Being with AI. Introducing virtual twin-driven AI models for medical diagnosis of a variety of diseases
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is generated and integrated in complex multicellular systems remains limited. Progress in the field requires the development of engineered multicellular models as mechanical reference systems, new
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. Collaborate with partners in signal processing and machine learning to link physics-based models with data-driven algorithms. Participate in joint research activities, publications, and dissemination through
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Assistant Professor, you will: Conduct research in the field of networked systems, focusing on distributed control, optimization, and data-driven modelling. Develop innovative methods for modelling, control
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scientist-engineer hybrid to deploy AI-driven discovery platforms directly with portfolio research teams. You'll bridge the gap between cutting-edge agentic AI systems and real-world drug discovery workflows
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focus on translational Research, Development & Deployment which focus on specific area of the energy value chain, and a number of Living labs and Testbeds which facilitate large scale technology