2026 Future Talent Program - Data Science or AI/ML - Co-op

Merck KGaA Darmstadt Germany • Cambridge, MA

105d • $39,600 - $105,500 • Onsite

About The Position

The Future Talent Program features Cooperative (Co-op) education that lasts up to 6 months and will include one or more projects. These opportunities in our Research and Development Division can provide you with great development and a chance to see if we are the right company for your long-term goals. There are two positions in the Artificial Intelligence Machine Learning (AI/ML) group. Candidates can apply for the opportunity to be involved in a project designed to enable students to further develop their skills and to evaluate if we are the right company for their long-term goals.

Requirements

• Candidates must be currently enrolled in a minimum of a Bachelor's degree program in Computer Sciences, Statistics, Biostatistics, Biological Engineering, Computational Biology, or a related field of study.
• Students enrolled in graduate programs (MS or PhD) are highly encouraged to apply.
• Candidates must be available to work full-time for 6 months in 2026.

Nice To Haves

• Experience with Python.
• Experience with the analysis of single-cell RNA-seq datasets.
• Demonstrated communication and interpersonal skills.
• Ability to work well in a collaborative team environment.
• Excellent academic achievement and analytical ability.
• Experience with modern deep learning tooling including PyTorch and/or JAX and GPUs.
• Experience with multi-GPU model training.
• Experience with cloud computing, AWS, and command line terminal.

Responsibilities

• Graph-based representational learning for biological inference.
• Construction and characterization of Graph Neural Networks.
• Integration of graph representations with omics-based foundation models.
• Develop methods and techniques to enable harmonization of metadata.
• Developing methods for improving the trainability and interpretability of foundation models.
• Building foundation models capable of better modeling perturbational biology.
• Developing multi-modal models to learn representations from multi-omic data.
• Exploring approaches for probing trained foundation models for learned biology.
• Optimal experimental design to learn predictive models in small data regimes.

Benefits

• Equal opportunities to all employees and applicants for employment.
• Prohibition of discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.
• Commitment to inclusion and diversity.

What This Job Offers

• Job Type: Full-time
• Career Level: Intern
• Industry: Chemical Manufacturing
• Education Level: Bachelor's degree