Senior/Staff AI Scientist, Target Discovery

This is a fully remote position, open to applicants in New York, +1 more state.

📋 Description

• Create, modify, and implement deep learning models that predict the effects of potential therapeutic interventions on both intra- and intercellular signaling.

• Design experiments that produce data necessary for training and validating systems biology models.

• Collaborate with Disease Biologists, Structural Biologists, Computational Biologists, and Wet Lab scientists to define and tackle indication-specific challenges.

• Develop in silico and in vitro validation strategies to enhance design and evaluation methodologies through iterative improvements.

• Effectively communicate and present experimental findings to various audiences, facilitating informed decision-making and advancing program development.

• Produce and publish impactful research that strengthens Absci’s position in the field of AI-driven antibody therapeutic discovery.

• Mentor and guide other Scientists and Engineers.

• Acquire new technical skills to enhance scientific contributions.

• Create and implement protein design models for antibody drug development.

• Leverage AI drug discovery expertise encompassing deep learning, protein design and engineering, drug discovery, natural language processing, computer vision, and molecular dynamics.

• Identify innovative therapeutic targets and generate candidate antibody therapeutics through in silico methods.

⛳️ Requirements

• PhD or equivalent experience in Machine Learning, Computer Science, Computational Biology, Computational Chemistry, Biophysics, or a related field.

• At least 3 years of post-graduate experience.

• Strong foundation in various areas including biological world models, mathematical biology, systems biology, disease biology, computational biology/multi-omics, and experiment design to create and/or manage intra- and intercellular perturbation datasets.

• Proficiency in Python and PyTorch.

• Expertise in designing and training large-scale model architectures.

• Mastery of appropriate scoring rules, validation metrics for highly imbalanced biological datasets, and active learning paradigms.

• Proven ability to collaboratively work in a dynamic, fast-paced, interdisciplinary environment.

• Demonstrated experience in conveying complex technical information to diverse audiences.

• Strong track record of publications in esteemed, high-impact journals and conferences.

• Legal authorization to work in the United States.

🏝️ Benefits

• Offers equity.

• Provides bonuses.

• Access to top-tier computational resources.

• Own Wet Lab for efficient design > build > test > learn cycles.

• Opportunity to witness your work translate into therapeutic benefits for patients.

• Flexibility for remote work with the option to work onsite at the New York City office or Vancouver, WA headquarters if within commuting distance.