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Two fully-funded 3-year PhD studentships are available in Neuromorphic and Bio-inspired computing at the interface between control engineering, electrical engineering, computational neuroscience
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Directed Energy Deposition (DED) process for metallic components. The PhD candidate will focus on edge computing and the application of AI for data analysis and for identifying correlations with ground truth
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Annual tax-free stipend of £22,780/year for 4 years, full coverage of tuition fees for UK/Home Students, plus training/travel funds Placed On: We invite applications for a fully funded PhD research
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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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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relevant monitoring activities organised each year.Candidates can review the admission process on the website: https://icn2.cat/en/careers/phd-programme/who-when-howHow to apply:All applications must be done
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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America, Asia or Africa). The PhD process will be accompanied by integration into TUM’s School of Life Sciences or School of Management and participation in the related Graduate School training programs
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recent large-scale capabilities in physics. Reliability, exploring uncertainty quantification and robust inference in machine learning. Explainability, leveraging identifiability and unique recovery
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Job Description If you are ambitious and seeking to contribute to developing novel chemistry for a sustainable future a possibility is right here for you. A 3-year PhD fellowship is available in