Research Scientist

Headquartered in Silicon Valley, we are a newly established start-up where a collective of visionary scientists, engineers, and entrepreneurs are dedicated to transforming the landscape of biology and medicine through the power of generative AI. Our team comprises leading minds and innovators in AI and biological science, pushing the boundaries of what is possible. We are dreamers who reimagine a new paradigm for biology and medicine.

We are committed to decoding biology holistically and enabling the next generation of life-transforming solutions. As the first mover in pan-modal Large Biological Models (LBM), we are pioneering a new era of biomedicine, with our LBM training leading to ground-breaking advancements and a transformative approach to healthcare. Our robust R&D team and leadership in LLMs and generative AI position us at the forefront of this revolutionary field. With headquarters in Silicon Valley, California, and a branch office in Paris and Abu Dhabi, we are poised to make a global impact. Join us as we embark on this journey to redefine the future of biology and medicine through the transformative power of Generative AI.

Our Science team is a talented group of interdisciplinary researchers focused on the extension, use, and integration of biological foundation models to solve the most important biomedical and biological problems. This is a unique opportunity to shape the direction of our applied research, contribute to groundbreaking discoveries, and accelerate real-world applications.

• Lead and contribute to the development, adaptation, and application of one or more of the following biological foundation models: sequence, structure, single cell, imaging, phenotype and more. Lead and contribute to the development, adaptation, and application of integrated biological foundation models that bridge modalities and scales
• Collaborate with internal and external research partners to extend model capabilities and translate cutting-edge methods into applied biological insights.
• Design and execute experiments leveraging pan-modal biological data, from single-cell and spatial transcriptomics to multi-omic datasets.
• Identify high-impact opportunities for model-driven discoveries, validation studies, and new biological use cases.
• Mentor junior researchers and contribute to a culture of scientific excellence and innovation.
• Communicate research outcomes in internal/external reports, presentations, and top-tier journals/conferences.

• MSc / PhD (or equivalent expertise) in Computational Biology, Machine Learning, Bioinformatics, or a related technical field.
• Proven track record in research and innovation in the AI for biology space as demonstrated through publications in top-tier AI/ML (e.g., NeurIPS, ICML, ICLR) and/or core biology (e.g., Nature, Science, Cell) venues.
• Experience developing and debugging deep learning models in PyTorch, JAX, or TensorFlow, ideally with an emphasis on generative models, graph neural networks, or large-scale biological data applications.
• Strong understanding of biological data modalities, including some of the following: Single-cell RNA-seq, Single cell epigenetic data, Structure data analysis, Analysis of biomedical imaging data, Human phenotype data or other modalities that are relevant to the human simulation vision.
• Passion for interdisciplinary research at the intersection of AI and Biology, and willingness to acquire domain-specific expertise.
• Motivated and self-directed, capable of operating in a fast-paced, startup environment.
• Familiarity with software engineering best practices (version control, documentation, testing) and a record of open-source contributions preferred.

• 3+ years of postdoctoral or industry experience applying ML to biological data.
• Experience with genomics, transcriptomics, or proteomics datasets and functional assays (e.g., ATAC, Hi-C, CAGE).
• Familiarity with multi-omics, health, or EHR datasets and public data repositories (NCBI, ENCODE, ENSEMBL, TCGA, UK Biobank).
• Experience integrating and curating biological datasets for model training or hypothesis generation.
• Knowledge of multimodal or multiscale models, including transformers, diffusion models, VAEs, or graph neural networks.
• Prior exposure to large-scale distributed training and inference environments, and ML on accelerators.
• Background in network or systems biology, including gene regulatory networks, clustering, and embedding algorithms.

At GenBio AI, you will be part of a global, interdisciplinary effort to revolutionize biology and medicine through Generative AI. You will work alongside world-renowned scientists and engineers from institutions such as CMU, MBZUAI, Stanford, ENS, and Inria, supported by a board that includes Nobel Laureates and Turing Award winners.

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.