Description

Boehringer Ingelheim is currently seeking a talented and innovative Co-Op to join our global Computational Biology and Digital Sciences (gCBDS) department at our Ridgefield, Connecticut facility. As a Co-Op, you will contribute to data analysis that will help us discover new therapies for immune diseases. You will explore Large Language Model and other AI approaches to assist with the analysis and integration of large multi-omics datasets to improve our understanding of disease mechanisms and to identify potential novel targets that may lead to the development of better treatments.

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, diversity and inclusion, mobility, networking and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for our employees.

Duties & Responsibilities

• Implement novel ML/AI algorithms, especially generative AI, for internal data analysis

• Leverage Large Language Model (LLM) to analyze and integrate transcriptomic, proteomic and other omic data from human subjects to further characterize disease mechanisms

• Assist with interpretation of results

• Communicate results within the gCBDS department and to biologists in the therapeutic area

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.

• Onsite/Flex*: This position is site based with flexibility for remote working. Working onsite a minimum of 2-3 days per week is required. Remote working norms will be clarified during the interview process.

Desired Experience, Skills and Abilities:

• Experience programming in R and Python, including the ability to write your own scripts

• Experience with Large Language Model and natural language processing

• Completed coursework in computational biology, especially molecular biology or bioinformatics

• Experience with Unix/command line tools is a plus

• Experience dealing with large amounts of data desirable

• Good communication skills

• Ability to work independently and as part of a team

• Good work ethic, ability to think creatively, and enjoyment of problem solving

Compensation Data

This position offers an hourly rate of $20.00 - $33.00 USD commensurate to the level of degree program in which an applicant is actively enrolled. For an overview of our benefits please click here (https://www.boehringer-ingelheim.com/us/careers/benefits-rewards) .

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.

All qualified applicants will receive consideration for employment without regard to a person’s actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.