Research Scientist
il y a 1 semaine
- PhD (or evidence of equivalent level of expertise) in Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, or a related technical field
- Proven track record in research and innovation demonstrated through contributions in top-tier AI/ML (e.g., NeurIPS, ICML, CVPR, ECCV, ICCV, ICLR) and/or core biology (e.g., Nature, Science, or Cell) journals and conferences
- Skilled in developing, implementing, and debugging deep learning methods/models in popular frameworks, such as PyTorch, JAX, or Tensorflow with an interest in generative models, graph neural networks, or large-scale deep learning applications
- A strong theoretical foundation (probabilistic models, statistics, optimization, graph algorithms, linear algebra) with experience building models ground up
- A passion for interdisciplinary research (with an emphasis on the intersection of AI and Biology), and willingness to acquire necessary domain knowledge
- Motivated and self-driven with the ability to operate with partial and incomplete descriptions of high-level objectives (as is typical in a start-up environment)
- Evidence of familiarity and utilization of software engineering best practices (version controlling, documentation, etc), and open-source contributions, especially if used by others
- 3+ years of post-PhD experience in an industry or postdoc role
- Prior experience working at either a start-up or top research industry labs (e.g., OpenAI, FAIR, Deepmind, Google Research)
- Hands-on prior experience working at the intersection of AI and Biology
- Experience in large-scale distributed training and inference, ML on accelerators
- Experience with genomics, transcriptomics, or proteomics data, particularly functional assays (e.g. ATAC, CAGE, Hi-C, …)
- Experience with complex data types, including multi-omics and health data (EHRs).
- Familiarity with public data repositories (NCBI, ENSEMBL, ENCODE, TCGA, UK Biobank) and experience curating datasets to answer specific scientific questions.
- Experience with methods development for afore-mentioned data types
- Experience with multimodal or multiscale models (even in other domains, e.g. remote sensing, medical imaging).
- Deep knowledge of one or more of the following: transformers, convolutional networks, discrete diffusion models, self-supervised learning, and co-embedding approaches.
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Research Scientist
il y a 2 semaines
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il y a 2 jours
Paris, Île-de-France Institute of Foundation Models Temps pleinAbout the Institute of Foundation Models We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy. As part of our team, you'll have the opportunity to work on...
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il y a 2 jours
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il y a 2 semaines
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il y a 7 jours
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il y a 2 semaines
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il y a 2 semaines
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il y a 7 jours
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