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Research Scientist (AI)_Interactome

Genbio. AI, Inc. (GenBio AI) is an innovative global startup dedicated to developing foundation models (FM) for biology.


We aim to train transformative FMs on pan-modal biological data at all levels. Our goal is to achieve comprehensive, actionable empirical understandings of the mechanisms underlying all organismal physiologies and diseases. This will pave the way for a new paradigm in drug design, bio-engineering, personalized medicine, and fundamental biomedical research, all powered by Generative Biology.

Our founding team consists of world-renowned scientists and researchers in AI and Biology from prestigious institutions such as CMU and Stanford, alongside prominent financial investors.


Our management team boasts strong technical and managerial backgrounds, hailing from top academic institutions in the US and France, including CMU, ENS, L’X, and Inria, as well as leading tech companies like Isomorphic and Meta. Additionally, our advisory board features Nobel Prize Laureates in Chemistry, Medicine, and Economics, Turing Award Laureates, and senior policymakers from the US and UK.

GenBio AI a true global effort from day one, is establishing offices in Palo Alto, Paris, and Abu Dhabi.


Job Requirements
  • PhD (or evidence of equivalent level of expertise) in Computer Science, Artificial Intelligence, Machine Learning, 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 JAX, TensorFlow, or PyTorch, with an interest in generative models, graph neural networks, or large-scale deep learning applications.
  • A strong theoretical foundation (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.


Qualifications
  • 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 Qualifications
  • Prior experience working with diverse biological datasets, including but not limited to bulk/single transcriptomics (e.g., RNA-Seq), epigenetic (e.g., ATAC/ChIP-Seq), proteomics/phosphoproteomics (e.g., mass-spec), and genetics (e.g., GWAS) datasets.
  • Familiarity with diverse biological networks, including but not limited to protein-protein interaction, gene-gene expression, and TF-Target Gene regulatory networks.
  • Prior experience developing algorithms for network/systems biology (e.g., network construction/inference, clustering, embedding, etc)
  • Familiarity with Graph ML frameworks, such as  Pytorch Geometric, Deep Graph Library (DGL), and Nvidia RAPIDS (cuGraph/cuML).
  • Hands-on experience with geometric deep learning models such as Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT).
  • Familiarity with traditional (e.g., TransE, RotatE, etc.) and deep (ULTRA) representation learning algorithms for large knowledge graphs


Join us as we embark on this journey to redefine the future of biology and medicine.

We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Average salary estimate

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$120000K
$180000K

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What You Should Know About Research Scientist (AI)_Interactome, GenBio AI

Are you ready to contribute to groundbreaking research at the intersection of AI and biology? Look no further than the Research Scientist (AI) position at Genbio AI, Inc. Our innovative global startup is at the forefront of developing foundation models for biology, enabling transformative discoveries through pan-modal biological data. At GenBio AI, you'll work alongside a team of world-renowned scientists from esteemed institutions like CMU and Stanford, all driven by a passion for unraveling the mysteries of organismal physiologies and diseases. Imagine your work paving the way for advancements in drug design, bio-engineering, and personalized medicine. We’re looking for someone with a PhD in Computer Science, Artificial Intelligence, or a related field, plus a solid background in research and innovation. If you've published in top-tier AI/ML or core biology journals, you might be exactly who we're looking for! You should feel comfortable developing, implementing, and debugging deep learning models, especially in frameworks like JAX or TensorFlow. We value interdisciplinary research and the ability to operate independently in a startup atmosphere. With exciting opportunities to work with diverse biological datasets and cutting-edge technologies, this position offers the chance to make a real impact in the field. Join us at Genbio AI, where your expertise can help redefine the future of biology and medicine! We're committed to fostering an inclusive environment and encourage candidates from all backgrounds to apply. Your journey to transformative scientific contributions starts here.

Frequently Asked Questions (FAQs) for Research Scientist (AI)_Interactome Role at GenBio AI
What are the primary responsibilities of a Research Scientist (AI) at Genbio AI?

As a Research Scientist (AI) at Genbio AI, you will lead innovative research in AI applied to biological data. Your key responsibilities include developing and debugging deep learning models, contributing to publications in renowned journals, collaborating with interdisciplinary teams, and working on large-scale data analysis to uncover insights that drive advancements in drug design and personalized medicine.

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What qualifications do I need to become a Research Scientist (AI) at Genbio AI?

To be considered for the Research Scientist (AI) role at Genbio AI, you should possess a PhD in Computer Science, AI, or a related field, with a minimum of 3 years of post-doctoral experience. A strong publication record in top-tier AI and biology journals is essential, along with hands-on experience with deep learning frameworks such as TensorFlow or PyTorch, and familiarity with biological datasets.

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What skills are essential for a Research Scientist (AI) at Genbio AI?

For the Research Scientist (AI) position at Genbio AI, essential skills include proficiency in deep learning frameworks, a strong theoretical foundation in statistics and algorithms, and experience with biological datasets. Additionally, familiarity with graph neural networks and willingness to dive into interdisciplinary research are crucial for success in this role.

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What is the work environment like for a Research Scientist (AI) at Genbio AI?

The work environment for a Research Scientist (AI) at Genbio AI is dynamic and collaborative, wherein you’ll be working alongside top-tier scientists and researchers in a startup atmosphere. Adaptability and a proactive mindset are vital, as the team is focused on pushing the boundaries of AI within biological research, fostering creativity and innovation.

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What impact can a Research Scientist (AI) at Genbio AI have in the field of biology and medicine?

A Research Scientist (AI) at Genbio AI has the potential to make significant contributions to the fields of biology and medicine. By leveraging AI technologies to analyze complex biological data, you can help facilitate breakthroughs in drug development, enhance personalized medicine strategies, and redefine our understanding of biological systems, ultimately leading to improved healthcare outcomes.

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Common Interview Questions for Research Scientist (AI)_Interactome
Can you describe your experience with deep learning frameworks relevant to the Research Scientist (AI) position?

When discussing your experience, focus on the specific frameworks you've worked with, such as TensorFlow or PyTorch. Provide examples of projects where you developed or debugged models, emphasizing any innovative approaches you've taken or challenges you've overcome.

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How have you contributed to interdisciplinary research projects?

Highlight your collaborative efforts in interdisciplinary projects, detailing how you bridged the gap between AI and biology. Mention specific examples of teams you’ve worked with, and the outcomes of those projects to demonstrate your ability to work across disciplines.

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What research contributions have you made in top-tier AI or biology journals?

Be prepared to discuss your most impactful publications, focusing on their significance in the field. Explain your role in the research process, methodologies used, and the implications of your findings on AI applications in biology.

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What interests you about generative models in the context of biology?

Share your thoughts on the potential of generative models to revolutionize biological research. Discuss any relevant projects you’ve conducted or insights you've gained regarding how these models can be applied to biological data.

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Describe a challenging project you've completed and the outcomes achieved.

When responding, choose a project that showcases your problem-solving skills and creativity. Discuss the challenge in detail, the steps you took to address it, and the results, ensuring to highlight any advancements in AI or biological understanding.

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What approaches do you take to ensure your research is applicable in real-world scenarios?

Talk about your methods for connecting research with practical applications. This might include collaboration with industry partners, seeking feedback from end-users, or looking into compliance and ethical considerations that can impact biological research.

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How do you stay updated on the latest trends in AI and biology?

Discuss your strategies for professional development, which could include attending conferences, subscribing to journals, participating in online forums, or engaging with the academic community through collaborations.

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What software engineering best practices do you utilize in your research?

Explain the importance of software engineering principles like version control, documentation, and testing in your workflow. Provide specific examples of how you've implemented these practices in past projects to enhance reproducibility and collaboration.

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Can you explain your experience with large-scale distributed training and inference?

Detail your experience with distributed systems and the technologies you’ve used for large-scale training. Discuss challenges faced in scaling models and strategies you've implemented to optimize performance.

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What excites you most about joining Genbio AI as a Research Scientist (AI)?

Articulate your passion for the intersection of AI and biology and how it aligns with Genbio AI’s mission. Share specific aspects of the company that resonate with you, such as their groundbreaking research initiatives or their commitment to diversity and inclusion.

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DATE POSTED
December 13, 2024

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