Machine Learning-guided Antibody Engineering Co-Op, Biotherapeutics
Description
Boehringer Ingelheim is currently seeking a talented and innovative Co-Op to join the Biotherapeutics Discovery department located at our Ridgefield, CT facility. The position offers an exciting opportunity to engage in the discovery and molecular engineering of Biotherapeutics for unmet medical needs. You will be an integral member of the Engineering group where you will contribute to the development Machine Learning (ML)-centric strategies for antibody engineering.
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
• Assist in the customization and application of ML and AI techniques to advance therapeutic discovery, particularly for novel and technically challenging biological modalities.
• Gain hands-on exposure to high throughput antibody engineering workflows, including protein expression, purification, and basic biophysical characterization.
• Apply foundational laboratory skills to support experimental studies, with a strong interest in contributing to and learning from experimental outcomes.
• Read, critically evaluate, and stay current with relevant scientific literature in computational biology, ML/AI, and therapeutic discovery, and communicate key insights to the project team.
• Develop a working understanding of project and research team objectives and contribute effectively toward shared goals.
• Collaborate with cross functional project teams, participating in discussions and representing computational or technical perspectives as appropriate.
• Contribute ideas and analyses that support expertise related components of broader program objectives while learning best practices in team based scientific research.
• Comply with all applicable regulations; ensure that work performed in area of responsibility is conducted in a safe and compliant manner; maintain proper records in accordance with SOPs and policies
• Prepare clear technical reports, publications and oral presentations; independently communicate results in the form of reports and/or presentations; present responsibly and defend own work at scientific meetings; deliver project updates to senior level management
• Contribute to departmental administration; demonstrate fiscal responsibility with respect to cost of experiments, technology, external collaborations, and travel
Requirements
• Must be a current undergraduate, graduate or advanced degree student in good academic standing.
• Student must be enrolled at an accredited college or university for the duration of the internship/co-op.
• 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/co-op.
• 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 Skills, Experience and Abilities
• Experience with machine learning approaches for protein engineering and modern data science platforms, including protein language models (pLMs), neural network–based model development, and Databricks-based workflows.
• Requires in-silico/computational skills including fluency in python, experience with scikit learn pytorch, or similar ML package implementations. Experience with Jira/ Bitbucket and version control best practices considered a plus.
• Basic laboratory knowledge and foundational experimental (wet-lab) skills.
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