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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | about 1 month ago
related to staff position within a Research Infrastructure? No Offer Description The Quantitative Genetics research group is interested in developing statistical genomics toolboxes to decipher the genetic
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autonomous robotic water-quality sampling at the University of British Columbia in Vancouver, Canada. We are developing a drone-based platform for rapid acquisition of in-situ water data at scale. We
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developments such as novel algorithms to support logistics operations, novel automation approaches or the design and development of new digital support tools for logistics providers. Significant flexibility
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The Faculty of Engineering, Department Elektronica en informatica, Research Group Electronics and Informatics: Research – Development - Innovation is looking for a PhD-student with a doctoral grant
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currently work at the LCSB. We excel because we are truly interdisciplinary, and together we contribute to science and society. Your role Multi-omics data integration and workflow improvement Development and
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scalable deployment Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches Design and run experiments using the latest ML tools and frameworks
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, and law, where inaccurate or misleading responses –- known as "hallucinations" –- can have serious consequences. ARMADA seeks to develop solutions that make these AI systems more trustworthy, coherent
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play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms
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consumption while guaranteeing optimal power production. You will work on the cutting edge of both wind energy and machine learning, two of the fastest growing scientific disciplines, to develop graph-based
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning