Absci - Senior/Staff AI Scientist, Antibody Design
Requirements
• PhD or equivalent experience in Machine Learning, Computer Science, Computational Biology, Computational Chemistry, Biophysics, or a related field • 3+ years of research experience at the intersection of machine learning and protein design, molecular modeling, or a related field, ideally including industry experience. • Fluency in Python and PyTorch • Comfortable with design, implementation, and evaluation of state-of-the-art AI algorithms for protein design and protein structure prediction • 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 [email protected].
Responsibilities
• Partner with team members across AI Research, AI Engineering, Computational Biology, and Protein Engineering to achieve success along the following axes: • Novel test-time compute strategies that maximize the quality and efficiency of our design pipelines. • Multi-objective optimization of therapeutic design goals • Solve key challenges of per-target design specification via innovative, AI-driven solutions. • Analyze in silico and in vitro validation results to iteratively improve design and evaluation methodologies • Develop, deliver and publish high-impact research that advances Absci’s position as a thought leader in the field of AI antibody design • Invest in ensuring work is accessible and interpretable to scientists with other domain expertise. • Ability and willingness to learn new technical skills to improve scientific contributions
Benefits
• $160K – $260K • Offers Equity • Offers Bonus • 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. • 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 located within commuting distance • 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
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