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Interaction with a design and data-oriented perspective. Experience in research in the domain of affective interaction design Background in large-scale data engineering Personal or professional experience
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, multimodal foundation models, continuous learning systems, or agentic AI models. Experience with state-of-the-art multimodal foundation models and agentic AI frameworks Experience in large-scale deep learning
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biochemistry, and large-scale genetic screening in our research approach. Basic Qualifications: 1. A Ph.D. in a relevant field 2. Demonstrated record of research achievement. 3. Strong written and oral
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, survival analysis), with willingness to develop further expertise experience conducting original research and engaging in scholarly activity ability to work with complex, large-scale cohort or clinical
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comprehensive excel spreadsheets to track progress; comprehensive data management as required by a large-scale RCT; liaisng with the trial steering committee; contributing to and leading on reports to the funder
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founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large
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, or similar ML frameworks Experience with large-scale training or inference of LLMs Interest in LLM alignment, reinforcement learning, or generative AI systems Fluency in English; clear communication, problem
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, proteomics, bioinformatics, or a related field Strong experience and a passion for mass spectrometry-based proteomics, computational biology, and large-scale data integration Interest in plant immunity
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are seeking a Biostatistician who will analyze large scale, longitudinal data. Analyzed data is abstracted and extracted from electronic health records, laboratory and pharmacy databases, and patient reported
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/f/d) starting October 1, 2027 The position will be created in the framework of the Cluster of Excellence 3121 “TERRA: Terrestrial Geo-Biosphere Interactions in a Changing World” , a large research