Research Scientist, Biologics

Proclinical; Massachusetts; On-site; USD 83,000 - 101,000; Part time

Job summary

Proclinical is seeking a Research Scientist specializing in AI and Machine Learning for biologics to join a fast-moving biotech environment on contract along the East Coast. You will contribute to the development of advanced computational frameworks and integrate ML into therapeutic discovery processes.

You will design and scale AI/ML solutions for antibodies, ASOs, and other modalities, build predictive models, curate datasets, and collaborate with multidisciplinary teams to accelerate

Qualifications

• PhD preferred in Computational Chemistry, Biology, ML, Biomedical/Chemical Engineering, or related field.
• Background in oligonucleotide chemistry and antibody design/characterization.
• Experience in computational modeling of antibody–antigen interactions, including sequence and structure analysis.
• Expertise in probabilistic learning, deep learning models (e.g., RNNs, GNNs, Transformers), and generative AI.
• Proficiency in Python, R, and SQL with PyTorch, TensorFlow, or scikit-learn.
• Experience developing ML models for DNA, RNA, and proteins, including language models and structure prediction.
• Familiarity with AWS, GitHub, Docker, and large-scale computing.
• Strong communication and collaboration skills.

Responsibilities

• Design and implement advanced AI/ML approaches for antibody discovery, including fine-tuning protein language models and creating generative protein design workflows.
• Develop and scale machine learning methods for optimizing antibodies, antigens, ADCs, and other biologic modalities.
• Build predictive models to prioritize ASO designs based on exon-skipping response across various targets and modalities.
• Create reproducible computational frameworks for biologics, including data ingestion, feature engineering, model training, validation, and deployment.
• Curate and harmonize datasets from internal and external sources, defining robust sequence and structure features to enhance model performance.
• Establish benchmarks and conduct prospective tests to assess model accuracy, robustness, and scalability. Collaborate with experimental teams to validate predictions.
• Evaluate and adopt proprietary and open-source tools to improve modeling workflows and decision-making processes.
• Maintain a clean, well-documented codebase and provide user guidance for cross-functional teams.
• Perform additional related tasks as needed.

Skills

Oligonucleotide chemistry

Antibody design

Computational modeling

Deep learning

Python

R

SQL

PyTorch / TensorFlow

Language models

Cloud computing

Data curation

Communication

Education

PhD preferred in Computational Chemistry, Biology, ML, Biomedical/Chemical Engineering, or related field

Tools

AWS

Docker

GitHub

Scikit-learn

Jupyter

Job description

Research Scientist AI/ML Biologics - Contract - East Coast

Help bring science to life and join a leading biotech company where you will play a key role in delivering impactful research that drives healthcare innovation!

Proclinical is seeking a Research Scientist specializing in AI and Machine Learning for biologics. In this role, you will contribute to the development of advanced computational frameworks.

Primary Responsibilities:

This position will be required to support the design and optimization of antisense oligonucleotides (ASOs) and biologics. You will play a key role in integrating machine learning and artificial intelligence into therapeutic discovery processes, helping to accelerate innovation across multiple modalities.

Skills & Requirements:

• Advanced degree (PhD preferred) in Computational Chemistry, Biology, Machine Learning, Biomedical/Chemical Engineering, or a related field.
• Strong background in oligonucleotide chemistry and antibody design/characterization.
• Proven experience in computational modeling of antibody-antigen interactions, including sequence and structure analysis.
• Expertise in probabilistic learning, deep learning models (e.g., RNNs, GNNs, Transformers), and generative AI.
• Proficiency in programming languages such as Python, R, and SQL, with experience using frameworks like PyTorch, TensorFlow, or scikit-learn.
• Experience developing machine learning models for DNA, RNA, and proteins, including language models and structure prediction.
• Familiarity with large-scale computing, cloud infrastructures, and database systems (e.g., AWS, GitHub, Docker).
• Strong communication and collaboration skills to work effectively with multidisciplinary teams.
• Commitment to continuous learning and a team-oriented mindset.

The Research Scientist's responsibilities will be:

• Design and implement advanced AI/ML approaches for antibody discovery, including fine-tuning protein language models and creating generative protein design workflows.
• Develop and scale machine learning methods for optimizing antibodies, antigens, ADCs, and other biologic modalities.
• Build predictive models to prioritize ASO designs based on exon-skipping response across various targets and modalities.
• Create reproducible computational frameworks for biologics, including data ingestion, feature engineering, model training, validation, and deployment.
• Curate and harmonize datasets from internal and external sources, defining robust sequence and structure features to enhance model performance.
• Establish benchmarks and conduct prospective tests to assess model accuracy, robustness, and scalability. Collaborate with experimental teams to validate predictions.
• Evaluate and adopt proprietary and open-source tools to improve modeling workflows and decision-making processes.
• Maintain a clean, well-documented codebase and provide user guidance for cross-functional teams.
• Perform additional related tasks as needed.

Compensation:

• $60 to $73 per hour.