Boehringer Ingelheim · 20 hours ago
Data Science Internship
United States
Internship
Remote
Intern
$20/hr - $33/hrBoehringer Ingelheim is a global leader in human and animal health, seeking a Data Science Co-op in the Biotherapeutics department. The role involves applying advanced machine learning techniques to enhance antibody engineering and biotherapeutic research while collaborating with experienced scientists and engineers.
BiotechnologyHealth CareMedicalPharmaceutical
No H1B
Responsibilities
Collaborate with the Biotherapeutics Data Science & AI team to develop and apply generative AI and protein language models for antibody discovery
Design and implement deep learning and machine learning models to support predictive analytics in biotherapeutics drug discovery
Analyze high-dimensional biological datasets (e.g., sequence, structure, assay data) to uncover insights that inform CMC strategies and improve developability
Assist in building scalable pipelines for model training, evaluation, and deployment in a research setting
Contribute to ongoing research projects by performing literature reviews, benchmarking algorithms, and presenting findings to cross-functional teams
Support the development of internal tools and platforms that accelerate biologics research through automation and intelligent data integration
Qualification
Required
Must be a current undergraduate, graduate or advanced degree student in good academic standing
Student must be enrolled at a college or university for the duration of the internship
Overall cumulative minimum GPA from last completed quarter/semester 3.0 GPA (on a 4.0 scale) preferred
Major or minor in related field of internship
Undergraduate students must have completed at least 12 credit hours at current college or university
Graduate and advanced degree students must have completed at least 9 credit hours at current college or university
Strong foundation in machine learning, deep learning, and statistical modeling, with coursework or project experience in bioinformatics or computational biology
Familiarity with protein sequence and structure data, and experience using advanced protein language models (PLMs) such as ESM-2
Exposure to structure prediction and generative design tools including AlphaFold, Rosetta, RFDiffusion, and ProteinMPNN
Experience working with antibody-specific and structural databases such as SAbDab, OAS, and PDB to support molecular modeling and developability assessments
Hands-on experience with graph neural networks (GNNs) for modeling biomolecular interactions and structural relationships
Familiarity with AI-driven approaches for modeling protein interactions, structural compatibility, and molecular design
Proficiency in Python and relevant libraries (e.g., PyTorch, TensorFlow, scikit-learn)
Ability to work independently and collaboratively in a multidisciplinary team environment
Must be legally authorized to work in the United States without restriction
Must be willing to take a drug test and post-offer physical (if required)
Must be 18 years of age or older
Preferred
Overall cumulative minimum GPA from last completed quarter/semester 3.0 GPA (on a 4.0 scale) preferred
Background or interest in antibody engineering, biologics developability, or CMC workflows is a strong plus
Company
Boehringer Ingelheim
Boehringer Ingelheim is a group of pharmaceutical companies that focuses on prescription medicines and animal health. It is a sub-organization of Boehringer Ingelheim.
Founded in 1885Ingelheim Am Rhein, Rheinland-Pfalz, DEU
10001+ employees
Funding
Current Stage
Late StageLeadership Team
Christian Eckermann
Corp. SVP BioPharma Network
Clemens Twardy
Corporate Vice President, Head of Global Supply Chain and Lifecycle Management Animal Health
Recent News
BioWorld Financial Watch
2026-02-02
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