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is using state of the art machine learning tools to extract interpretable latent dynamics. We seek a highly motivated PhD student to develop a predictive computational model using recurrent neural
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Your Job: In this position, you will be an active part of our AI Consulting Team. Together with our partners, we develop new and innovative applications of Machine Learning. You will connect
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developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra. Desirable: - knowledge in the field of Planetary Sciences - very good written and spoken English (C1
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Max Planck Institute for Brain Research, Frankfurt am Main | Frankfurt am Main, Hessen | Germany | about 5 hours ago
neuroscience Strong analytical and critical thinking skills A willingness to learn new techniques, including advanced experimental methods and computer programming Excellent verbal and written communication
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novel machine learning-guided approaches. The position is located at TUM Campus Heilbronn. Your qualifications Strong background in computer science, AI, or related areas or similar fields. Solid
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, as well you know how to work with a computer You work as a team player to solve problems analytically and work out solutions You are willing to learn something new every day and are willing to participate
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from the vibrant research community around machine learning of the SCADS.AI center ( https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in the Climate Change
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community around machine learning of the SCADS.AI center (https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in the Climate Change Era. We aim to attract the best
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essential. Good programming skills in at least one programming language (e.g., Python). Experience with machine learning, LLMs, or HCI/user study methodologies will be a plus. Strong interest in acquiring and
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multi-omics data integration and the project will provide opportunities to learn, develop, and apply machine learning and deep learning methods on genomics data. Requirements: excellent university and PhD