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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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and waste heat sources will need to integrate multiple supply options with varying temperature levels. To support effective planning, energy professionals at the district and city level must be able
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explored using scientific machine leaning. Machine learning, programming experience and a curious mind-set You are fascinated by how computers can learn from data and you have a strong interest in the
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integrated into the International PhD Programme (IPP; https://www.imb.de/phd ), which is organized by IMB ( www.imb.de ). The IPP offers an exciting, interdisciplinary and lively international community
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-RTG PhD student, you will be integrated into the International PhD Programme (IPP; https://www.imb.de/phd ), which is organized by IMB ( www.imb.de ). The IPP offers an exciting, interdisciplinary
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Supervisors: Professor Richard Hague1 , Professor Chris Tuck1 , Dr Geoffrey Rivers1 (1 Faculty of Engineering) PhD project description: Inkjet printing allows multiple materials to be 3D-printed
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generated data sets of different sizes and measuring the environmental impact. This impact can be measured and calculated by our Software Energy Lab, which has multiple test machines with GPUs and AI
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represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster networking, enable internationalization and
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. Candidates should have a strong record of scholarly activity. Candidates whose research complements existing department programs are preferred. Details regarding our research programs and faculty can be found
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project description: Inkjet printing allows multiple materials to be 3D-printed simultaneously, useful for printing functional devices. Discovering the interactions of these materials and how to leverage