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Data Science Co-Op

Description

Boehringer Ingelheim is currently seeking a talented and innovative Intern to join our Department Name department located at our insert your location facility. As an Intern, you will a few sentences describing the basic purpose of the internship. As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies´ success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for ouremployees.

Duties & 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.

Requirements

•    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.

 

Desired Experience, Skills and Abilities:

 

  • 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).
  • Background or interest in antibody engineering, biologics developability, or CMC workflows is a strong plus.
  • Ability to work independently and collaboratively in a multidisciplinary team environment.




Eligibility Requirements
•    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

Compensation Data

This position offers an hourly rate of $20 to $33 commensurate to the level of degree program in which an applicant is actively enrolled. For an overview of our benefits please click here

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