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to improve and optimize stem cell differentiation and manufacturing. As our new colleague you will be part of a diverse and multi-disciplinary team, which is engaged in machine learning and has a drive to make
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the detection of extinct or extant life, and directly inform the optimization of flight-ready instruments and science strategies. Coordinated research modules will start with construction of a 1000+ sample set of
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, testing, optimizing, benchmarking and validating custom machine learning algorithms for multi-dimensional remote sensing applications Good social skills, meaning that you enjoy collaborating with others in
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Mathematics, or a closely related field. Design and optimize multimodal LLMs to encode, fuse, and reason over heterogeneous scientific data from diverse modalities such as numerical tables, text, and images
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databases. · Troubleshoot experimental systems and optimize assays. · Prepare manuscripts, reports, and contribute to grant proposals. · Mentor graduate and undergraduate trainees. · Maintain compliance with
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | 1 day ago
systems optimized for integrating behavior, physiology, and computational analysis, including immersive Virtual Reality (VR) laboratories developed for animal experiments, and real-time behavioral tracking
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conducted within a consortium of laboratories based in Paris. Mission The successful candidate will design, conduct, and coordinate complex experimental work, including optimization of gene expression tools
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workflows, and data engineering for mobility platforms • AI/ML for transportation prediction, system optimization, and environmental/health impact modeling • Deployment of decision-support tools for public
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, Sputtering or MOCVD systems for microelectronics and emerging sensor technologies. Key Responsibilities: Develop and optimize wafer-scale 2D materials, including TMDCs, MXenes, and MOFs, for microelectronics
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) or discrete manufacturing (e.g., electronics assembly, automotive, home appliances). Explore the integration of large language models and reinforcement learning for real-time optimization, fault self