Material and Analytical Sciences - Co-Op

Description

Boehringer Ingelheim is currently seeking a talented and innovative Co-op candidate to join our Material and Analytical Sciences department located in Ridgefield CT. As a Co-op, you will tackle cutting edge research in development of a machine learning program to advance, have pharmaceutical development exposure, enjoy both personal and team accomplishments through collaboration with analytical scientists and computational chemists.

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

• Develop a machine learning tool with small data.

• Work with Analytical chemists to build a training set of experimental data

• Mine literature for relevant data to augment training set.

• Maintain awareness of the competitive landscape of peer-reviewed publications to advance knowledge database.

• Assist with design of experiments to enable capture of relevant data for model building.

• Writes reports and adheres to protocols to meet objectives in a timely manner.

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 organic chemistry background.

• Familiar with molecular modeling programs and structural chemistry concepts.

• Proficient in design and implementation of machine Learning tools in a chemistry environment.

• Working experience with software from companies such as Chemical Computing Group, Schrodinger, Gaussian, Molsof, Chemaxon, Knime, RDKit and ICM Molsoft

• Experience with machine learning/AI to rationalize chemical reaction propensities and recommend actionable hypotheses.

• Ability to build predictive ML/AI-based models to find and score likely outcomes.

• Knowledge of computing infrastructure is a plus.

• Background in training set design, diversity analysis, and approaches to link ML with DFT programs is strongly preferred.

• Stays current with literature in identifying emerging science to advance computational platforms.

• Excellent documentation and record keeping skills.

• Ability to communicate clearly and effectively in oral and written format.

• Work independently and in a team environment.

Compensation Data

This position offers an hourly rate typically between $20/ hour and $33/ hour commensurate to the level of degree program in which an applicant is actively enrolled. For an overview of our benefits please click here. (~~~)

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.