Research Scientist (AI) - Sequence jobs in United States
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GenBio AI · 2 days ago

Research Scientist (AI) - Sequence

GenBio AI is a newly established start-up headquartered in Silicon Valley, focused on transforming biology and medicine through generative AI. The Research Scientist (AI) role involves leading research and innovation at the intersection of AI and biology, contributing to groundbreaking advancements in biomedicine.

Artificial Intelligence (AI)BiotechnologyMedical
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H1B Sponsor Likelynote

Responsibilities

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

Qualification

Deep LearningGenerative AIComputational BiologyMachine LearningPyTorchJAXTensorFlowProbabilistic ModelsGraph AlgorithmsLarge-scale TrainingInterdisciplinary ResearchSoftware Engineering PracticesOpen-source ContributionsMotivatedGenomicsMulti-omics DataPublic Data RepositoriesTransformersConvolutional NetworksSelf-supervised LearningSelf-driven

Required

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

Preferred

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

Company

GenBio AI

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GenBio AI creates AI-driven models to simulate and predict biological systems at multiple scales.

H1B Sponsorship

GenBio AI has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (3)
2024 (1)

Funding

Current Stage
Early Stage
Company data provided by crunchbase