Cellarity seeks a Machine Learning Scientist to develop and advance foundation models that capture biological networks driving cellular dysfunction and integrate diverse perturbation modalities to accelerate drug discovery.
Requirements
- Strong foundation in statistics, deep learning and generative AI.
- Proficient in Python and scalable ML frameworks (e.g. PyTorch, Hugging Face)
- Experience with high-dimensional biological data analysis (bulk/single-cell RNA-seq, Gene regulatory networks, PPI networks, multi-omics integration).
- Experience with chemical / CRISPR perturbation screen data (eg: Perturb-seq).
- Experience developing deep generative models for representation learning.
- Experience efficiently training and fine-tuning foundation models on omics data.
- Experience with cloud computing (AWS/GCP) and MLOps best practices.
Responsibilities
- Design and implement novel algorithms and architectures for large-scale foundation models (e.g. Diffusion models, Transformers, VAEs) using single-cell RNA-seq and other modalities.
- Develop mechanistic interpretability methods to infer gene networks and regulatory mechanisms via attention, graph-based, and/or causal representation methods.
- Build state-of-the-art perturbation models using multi-modal perturbation (small molecules, CRISPR, cytokines) and phenotypic data.
- Pre-train, post-train and deploy generative AI models using proprietary datasets, and distributed training and inference on cloud platforms.
- Establish clinically relevant benchmarking and evaluation frameworks to assess context generalization and guide model improvements.
- Stay current with the latest research in foundation models, representation learning (across biology, NLP, vision, and audio), and perturbation modeling.
- Collaborate with interdisciplinary scientists from biology, chemistry, and technology teams to translate research questions into cutting-edge ML solutions.
Other
- PhD in Computer Science, Computational Biology, or related field, OR Master's degree with 3+ years of relevant ML research or industry experience.
- Excellent communication skills and ability to work in interdisciplinary teams.
- Ability to work in a fast-paced, multidisciplinary, biotech environment.
- Communicate technical concepts clearly to diverse scientific audiences.
- Contribute to strategic roadmap planning and technical decisions.
