Spring Machine Learning Co-Op/Internship, Medicinal Chemistry (Drug Discovery)

Job Description

Job Description

Title: Spring Machine Learning Co-Op/Internship

Location: Downtown Boston, MA (on-site 4 days/week)

Duration: January-June 2026

Hourly Rate: $25-$35/hr, dependent on experience

Weekly Hours: 30-40 hours/week

Job Summary:

Antares Therapeutics is seeking a highly motivated machine learning co-op student to join the Discovery Predictive Sciences team for the spring semester of 2026. The Discovery Predictive Sciences team is tightly integrated with drug discovery project teams, and bridges machine learning, medicinal chemistry, computational chemistry, and protein and structural sciences. The successful candidate will work with ML scientists to develop and implement new machine learning methods that will advance drug discovery efforts in medicinal chemistry.

Key Responsibilities:

• Implement state-of-the-art graph neural network (GNN) and transformer models from recently published literature.
• Benchmark model performance on in-house molecular property prediction tasks (primarily ADME).
• Design novel ML architectures and methods.

Basic Requirements:

• Bachelors degree or 2+ years of undergraduate education in Computer Science, Applied Math, Statistics, Data Science, Physics, Chemical Engineering, or a related field.
• Understanding of ML fundamentals and deep learning, e.g. graph neural networks (GNNs), diffusion models, and transformers.
• Experience with Python and ML frameworks (e.g. PyTorch, PyTorch Lightning, TensorFlow).
• Familiarity with code versioning (e.g. Git/GitHub).

Nice to have:

• Prior internship or co-op experience.
• Formal coursework in organic chemistry and/or biochemistry.
• Experience with cheminformatics toolkits (e.g. RDKit).

• Hands-on experience with AWS infrastructure, including SageMaker, S3, ECR.