Senior/Staff AI Scientist, Target Discovery
Absci
Data-first AI drug creation platform designing therapeutics for hard targets.
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About Absci
Absci is a clinical-stage biotechnology company advancing novel therapeutics using generative AI. Our Integrated Drug Creation™ platform combines cutting-edge AI models with a synthetic biology data engine, enabling the rapid design of innovative therapeutics that address challenging therapeutic targets.
Absci is a global company headquartered in Vancouver, WA, and maintains offices in New York City, Switzerland, and Serbia. Learn more at www.absci.com or follow us on LinkedIn (@absci), X (@Abscibio), and YouTube.
About the role
Absci is looking for a Senior/Staff AI Scientist to advance and deploy protein design models for antibody drug design. In this role, you will apply your broad expertise across specialized disciplines in AI Drug Discovery. We are looking for exceptional contributors with backgrounds in deep learning, protein design and engineering, drug discovery, natural language processing, computer vision, and molecular dynamics to develop innovative approaches to creating and assessing therapeutic antibodies in silico.
Absci offers AI Scientists a unique opportunity to both develop novel, cutting edge machine learning models and apply these models directly to identify novel targets, unlocking previously intractable disease interventions, and to generate candidate antibody therapeutics.
This is a remote position, with the option to work onsite at our New York City office or our Vancouver, WA headquarters if within commuting distance
Why Absci’s AI team?
Absci offers AI Scientists a unique opportunity to both develop novel, cutting edge machine learning models and apply these models directly to identify novel targets, unlocking previously intractable disease interventions, and to generate candidate antibody therapeutics. In particular we:
Provide our AI Scientists with access to industry-leading compute resources, enabling large-scale experimentation for model training and deployment
Maintain our own Wet Lab, enabling AI Scientists to validate novel modeling methods via rapid design > build > test > learn cycles
Developed and are growing our own pipeline of clinical-stage assets, enabling AI Scientists to see their work directly translated into therapeutic impact for patients
Key Responsibilities
Develop, adapt, and deploy deep learning models that predict the intra- and intercellular signaling effects of potential therapeutic interventions
Design experiments which generate data to train and validate systems biology models
Collaborate closely with cross-functional teams comprising Disease Biologists, Structural Biologists, Computational Biologists, and Wet Lab scientists to define and address the problem space within specific indications
Develop in silico and in vitro validation approaches to iteratively improve design and evaluation methodologies
Communicate and present experimental results in a manner that is accessible to audiences with highly-diverse backgrounds, driving discussions that lead to high-quality, informed decision-making and program progression
Deliver and publish high-impact research that advances Absci’s position as a leader in AI-guided antibody therapeutic discovery
Actively develop organizational talent through coaching and mentoring other Scientists and Engineers
Ability and willingness to learn new technical skills to improve scientific contributions
Qualifications
PhD or equivalent experience in Machine Learning, Computer Science, Computational Biology, Computational Chemistry, Biophysics, or a related field
Seasoned deep learning expert with 3+ years of post-graduate experience and a strong background in several of the following areas: biological world models, mathematical biology, systems biology, disease biology, computational biology/multi-omics, experiment design to generate and/or handling intra- and intercellular perturbation datasets
Fluency in Python and PyTorch
Expertise in large-scale model architecture design and training
Mastery of proper scoring rules, validation metrics for highly imbalanced biological datasets, and active learning paradigms.
Demonstrated ability to work collaboratively in an ambitious, fast-paced, interdisciplinary environment
Demonstrated experience presenting complex technical work to diverse audiences
Strong publication record in respected, high-impact journals and conferences
Legal authorization to work in the United States is required. Absci is committed to equal employment opportunity and non-discrimination for all employees and qualified applicants without regard to a person's race, color, sex, sexual orientation, gender identity or expression, age, religion, national origin, ancestry, ethnicity, disability, veteran status, genetic information, marital status, or any characteristic protected under applicable law. Any applicant requiring an accommodation in connection with the hiring process and/or to perform the essential functions of the position for which they have applied should make a request to the recruiter or hiring manager, or contact hiring@absci.com.