Principal Scientist - Computational Biologist and AI/ML Researcher
About the position Responsibilities • Develop and deploy ML models that deepen our understanding of complex biological systems in health and disease. • Promote open science through publishing papers and open-source code. • Collaborate with teams of scientists, computational biologists, and software engineers within the Allen Institute and external partners. • Advance community standards for scalability in developing, disseminating, and evaluating AI/ML/computational methods for scientific problems. • Lead the development of state-of-the-art engineering infrastructure at the Allen Institute to support AI/ML research and applications. • Stay up-to-date with the latest advancements in AI/ML and their potential applications in biological research. • Foster a collaborative and inclusive work environment that values diversity and encourages participation from team members with different voices, experiences, and backgrounds. • Mentor and guide junior researchers, interns, or students working on AI/ML projects related to biological research. • Participate in institute-wide initiatives, workshops, and seminars to promote cross-disciplinary collaboration and knowledge sharing. Requirements • PhD in Computer Science, Applied Mathematics, Computational Biology, Statistics, Biostatistics or similar field; or equivalent combination of degree and experience. • 11 years of equivalent experience. • Demonstrated ability to design, implement and apply AI/ML models for the analysis of large-scale biological data. Nice-to-haves • 15+ years of experience developing and applying ML methods. • Strong publication record of innovative scientific accomplishments (both individual and team). • Expertise in Python-based ML libraries and frameworks such as PyTorch, Jax, Pyro, NumPy, and Pandas. • Solid understanding of statistical analysis, data preprocessing, feature selection, and model evaluation techniques. • Experience building data pipelines to make biological data ML-ready, pipeline for model training and evaluation. • Knowledge of data preprocessing, normalization, and integration techniques specific to biological and clinical datasets. • Experience with distributed computing for ML models, (e.g. distributing load across multiple nodes, Ray, HPC, Distributed PyTorch, etc.). • Experience with data visualization and presentation of complex biological findings to both technical and non-technical audiences. • Strong problem-solving skills and ability to develop innovative computational approaches to address complex biological questions. • Proven ability to work independently and manage multiple projects simultaneously while meeting deadlines. • Excellent written and verbal communication skills, with the ability to collaborate effectively in a multidisciplinary team environment. Benefits • Medical insurance • Dental insurance • Vision insurance • Basic life insurance • 401k plan • Paid time off Apply tot his job Apply tot his job