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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 13 days ago
conservation related consequences of animal navigation, and (4) links biological and technical systems through models, algorithms, and devices. The acquired knowledge can help to solve major societal questions
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of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software using state-of-the-art AI technologies Ensuring the sustainability and
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | 19 days ago
on particulate and dissolved organic matter from hyperspectral absorption data sampled at Arctic expeditions at AWI’s Hausgarten (Fram Strait) in the last 10 years by optimizing established algorithms from
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group focuses on developing strategies and algorithms to quantity biologic effects of particle radiation based on underlying physics, biology and physiology. Within the BMFTR funded project “BIOMICRO
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format for the unambiguous and machine-readable characterization of software interfaces and data models Selection and configuration of algorithms for annotating and organizing research data and software
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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learning (ML) methods—including surrogate modelling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor
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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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Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | about 1 month ago
architecture of important crop traits like grain yield heterosis. In the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms