Senior/Staff AI Scientist, Target Discovery

Key Responsibilities:
- Develop, adapt, and deploy deep learning models that predict intra- and intercellular signaling effects of potential therapeutic interventions.
- Design experiments to generate data that train and validate systems biology models.
- Collaborate with cross-functional teams (Disease Biologists, Structural Biologists, Computational Biologists, 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 to diverse audiences to drive high-quality decision-making and program progression.
- Deliver and publish high-impact research advancing AI-guided antibody therapeutic discovery.
- Coach and mentor other Scientists and Engineers.
- Learn new technical skills to improve scientific contributions.

Qualifications:
- PhD (or equivalent experience) in Machine Learning, Computer Science, Computational Biology, Computational Chemistry, Biophysics, or related field.
- 3+ years post-graduate experience; strong background in several areas: biological world models, mathematical biology, systems biology, disease biology, computational biology/multi-omics, experiment design, and/or intra-/intercellular perturbation datasets.
- Fluency in Python and PyTorch.
- Expertise in large-scale model architecture design and training.
- Mastery of scoring rules, validation metrics for highly imbalanced biological datasets, and active learning paradigms.
- Demonstrated collaboration in an ambitious, fast-paced, interdisciplinary environment.
- Experience presenting complex technical work to diverse audiences.
- Strong publication record in high-impact journals and conferences.

Skills/Experience Mentioned:
- Deep learning, protein design and engineering, drug discovery, natural language processing, computer vision, and molecular dynamics.

Compensation Range:
- $160K - $260K