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neural networks, enabling us to estimate the reliability of a single decision of this algorithm. Regarding generalisation, recent self-supervised learning paradigms have strong synergies with the multi
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. Functional testing of developed PCBs, including experimental validation of electronic circuits and S-parameter characterization using a vector network analyzer (VNA).; 4. Experimental characterization
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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training, as well as career development support Joining ISTA’s and the NOMIS Foundation’s global networks of exceptional, pioneering researchers Proposals are invited in the following fields: Biology
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to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job
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. International experience and networks are also appreciated. We offer The positions will be filled for a fixed-term period of 1,5 years. The start date should be as soon as possible (during fall 2025). A trial
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, the ability to lead a research group, activities in Finnish or international research groups or networks, and experience in the acquisition of research funding. B. Evidence of public engagement. WHAT WE OFFER
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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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-life environments. The Role: As Research Fellow on the COG-MHEAR project, you will have the opportunity to use your strong background in deep neural networks and multimodal hearing-aid signal processing
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comparable estimates of health loss due to diseases, injuries, and risk factors worldwide. This role offers an opportunity to be part of a global network advancing data-driven health policy and research impact