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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Post-doc on formal verification and algorithm discovery for numerical analysis About us and our
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performance of large-scale experiments. LLM post-training and Reinforcement Learning Support SFT, preference optimization, and reinforcement learning workflows. Build and run RL environments for tasks with
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoctoral Position in Computational Genomics, Machine Learning & Single-Cell Biology Mission
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: 01.08.2026 Activity Rate : 50 - 70% Contract Type: CDD Duration: 1 year, renewable Reference: 2311 Contact For complementary information, please contact Prof. Tobias Kippenberg per e-mail: tobias.kippenberg
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Postal Code 1700 STATUS: EXPIRED X (formerly Twitter) Facebook LinkedIn Whatsapp More share options E-mail Pocket Viadeo Gmail Weibo Blogger Qzone YahooMail
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with a focused on micro-technologies. To strengthen our research program on laser-based methods to tailor material properties, we are looking for a post-doc to investigate advanced wavefront shaping
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and associated environmental impacts. Contribute to short-term (2026 to 2030) and long-term (2030 to 2050) verticalisation forecasting models based on machine learning, and to their validation against
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on developing new generative modeling approaches, scalable training algorithms, and foundation model technologies. The role is suited for candidates with a strong machine learning background who are excited
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architecture development: novel pretraining objectives, tokenization, and scalable architectures for biological data. Multimodal learning: representation learning across diverse biological data modalities
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the expertise, methods, and software to enhance privacy, data protection, and transparency; notably by the use of cryptography, blockchains and smart contracts, machine learning, software verification, device and