AI Scientist, Drug Creation

• Absci provides its AI Scientists with access to industry-leading compute resources, enabling large-scale experimentation for model training and deployment.
• Absci maintains its own Wet Lab, enabling AI Scientists to validate novel modeling methods via both in silico and in vitro experimentation.
• Absci maintains and is growing its own internal pipeline of assets, enabling AI Scientists to see their work directly translated into therapeutic impact for patients.

• Care as much about solving the technical problems related to designing antibody therapeutics as they do about translating solutions to the clinic;
• Use their expertise to influence the AI team's research agenda while maintaining high levels of responsibility and accountability for their work;
• Demonstrate their curiosity about the problems we are attempting to solve by developing proficiency in disciplines that fall outside their own areas of expertise, constantly increasing the scale and impact of their contributions;
• Invest in ensuring their work is accessible and interpretable to scientists with other domain expertise.

• Collaborate closely with cross-functional teams comprising disease biologists, Structural Biologists, Wet Lab scientists, and computational biologists to define antibody design criteria and deliver AI designs that meet drug creation program goals and target product profiles
• Adapt and deploy deep learning models for structure-based antibody design, antibody sequence design, antibody-antigen co-folding, antibody-antigen binding prediction, and physics-based antibody design and evaluation in real-world drug design campaigns
• Collaborate closely with Wet Lab scientists and Structural Biologists to design and deliver AI antibody libraries and associated Wet Lab workflows that enable in vitro assessment of model performance
• Analyze in silico and in vitro validation results 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 at the forefront of Wet Lab-integrated AI antibody discovery

• 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
• Demonstrated experience in developing and applying molecular simulation and/or computational biophysics tools
• Fluency in Python and familiarity with PyTorch
• Comfortable with design, implementation, and evaluation of state-of-the-art AI algorithms for protein design and protein structure prediction
• Expertise in large-scale model deployment
• Demonstrated ability to work collaboratively in an ambitious, fast-paced, interdisciplinary environment, including with Wet Lab scientists.
• Demonstrated excellence in cross-disciplinary communication and collaboration, and in presenting complex technical work to diverse audiences
• Strong publication record in respected, high-impact journals and conferences
• Basic understanding of the drug discovery process with an earnest desire to learn more

AbSci