RESEARCH SCIENTIST (AI/ML BIOLOGICS) @ PROCLINICAL
Join a pioneering team as a Research Scientist specializing in AI and Machine Learning for Biologics. In this role, you will be at the forefront of transforming the future of therapeutics by applying cutting-edge machine learning techniques to real-world biological challenges. Your work will focus on pushing the boundaries of antisense oligonucleotides, antibodies, and biologics discovery, contributing to a revolutionary approach in drug development and sequence-aware modeling.
Your primary responsibilities will include building scalable and reproducible AI/ML frameworks designed to accelerate the drug discovery process from initial research to therapeutic application. You will develop predictive models specifically tailored for oligonucleotide therapeutics and contribute to next-generation antibody discovery through advanced modeling of molecular sequences, structures, and interactions. This role is based in Cambridge, MA, with a flexible remote structure that includes occasional onsite visits to facilitate collaboration and laboratory synergy.
Your primary responsibilities will include building scalable and reproducible AI/ML frameworks designed to accelerate the drug discovery process from initial research to therapeutic application. You will develop predictive models specifically tailored for oligonucleotide therapeutics and contribute to next-generation antibody discovery through advanced modeling of molecular sequences, structures, and interactions. This role is based in Cambridge, MA, with a flexible remote structure that includes occasional onsite visits to facilitate collaboration and laboratory synergy.
Key Requirements
3+ years of post-PhD industry experience in a relevant scientific field.
Proven expertise in ASO, siRNA, and/or antibody design and development.
Strong foundation in modern AI/ML tools, approaches, and statistical modeling.
Proficiency in programming languages such as Python or R for data analysis.
Experience with deep learning frameworks like PyTorch, TensorFlow, or Keras.
Strong understanding of structural biology and protein-ligand interactions.
Demonstrated ability to build scalable and reproducible computational frameworks.
Excellent communication skills to present technical concepts to cross-functional teams.
Track record of scientific publications or patents in AI/ML or Biologics.
Ability to manage multiple projects in a fast-paced drug discovery environment.