Scientific Software Engineering Co-Op - Computational Chemistry & Spectroscopy

Boehringer Ingelheim; Ridgefield (CT); On-site; USD 33,000 - 45,000; Part time

Benefits offered by this job

Medical coverage

Paid time off

Disability and life insurance

Job summary

Boehringer Ingelheim Pharmaceuticals, Inc. in Ridgefield, CT is seeking a talented Intern to join the Materials and Analytical Sciences department.

You will help scale an IR assignment engine into a production-ready, user-facing application for pharmaceutical solids as part of a co-op. You will work on predicting IR band positions using structure-based and ML approaches, exploring ML/cheminformatics, and building an automated reporting and benchmarking pipeline while collaborating across

Qualifications

• Current undergraduate, graduate, or advanced degree student in good academic standing.
• Enrolled at an accredited college/university for the duration of the co-op.
• Minimum 3.0 GPA (4.0 scale) preferred.
• Major or minor in a related field for co-op.
• UG: at least 12 credit hours completed; Grad/Advanced: at least 9 credit hours.

Responsibilities

• Scale an IR assignment engine into a user-facing app analysts can run.
• Predict and rationalize IR band positions for solids with structure-based approaches.
• Explore ML/cheminformatics to improve predictions across classes.
• Implement deterministic execution: config, validation, logging, versioning.
• Automate generation of review-ready IR reports.
• Build a benchmark set from spectra and SME-verified data.
• Create an integrated pipeline from structure to reports.
• Present progress in meetings and contribute to reports.

Skills

Python for science

ML & AI methods

Data analysis

Communication skills

Independent & collaborative

Education

Undergrad/grad student in good standing

Enrolled for duration of co-op

GPA 3.0+ (4.0 scale)

Major/minor in related field

12 credit hours (UG)

9 credit hours (Grad)

Tools

Streamlit

FastAPI

Flask

python-docx

Jinja2

LaTeX

RDKit

scikit-learn

PyTorch

Git

Docker

conda

Job description

Boehringer Ingelheim is currently seeking a talented and innovative Intern to join our Materials and Analytical Sciences department located at our Ridgefield, CT facility. As a co-op, you will help turn a working, structure-constrained IR assignment engine into a scalable, production-ready application for pharmaceutical solids.

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 our employees.

Duties & Responsibilities

• Scale the existing structure-constrained assignment engine into a robust, documented, user-facing application that analysts can run independently
• Predict and rationalize characteristic IR band positions for pharmaceutical solids using structure-based and, where relevant, QM/MLIP approaches
• Explore machine learning and cheminformatics approaches to complement first-principles predictions and improve assignment accuracy across functional-group classes
• Implement deterministic, reproducible execution: configuration control, input validation, logging, error handling, version tagging and audit-friendly output
• Automate generation of review-ready IR assignment reports
• Build a curated benchmark set from portfolio spectra and SME-verified assignments
• Build one integrated pipeline that takes structural input, processes spectra, predicts assignments and generates review-ready reports automatically.
• Present progress and final results in section and departmental meetings and contribute to internal reports or publications where appropriate

Requirements

• Must be a current undergraduate, graduate or advanced degree student in good academic standing.
• Students must be enrolled at an accredited college or university for the duration of the 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 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:

• Excellent programming skills, particularly in Python for scientific computing (NumPy, SciPy, pandas, RDKit or equivalent)
• Experience building small applications or workflows (e.g. Streamlit, FastAPI, Flask) and automated document/report generation (python-docx, Jinja2, LaTeX or similar)
• Familiarity with machine-learned interatomic potentials and ML frameworks (scikit-learn, PyTorch)
• Familiarity with version control (Git) and reproducible environments (conda, Docker) with good software and data-management practice
• Solid understanding of molecular structure-spectra relationships and structural analysis/molecular modelling concepts
• Strong data-analysis and benchmarking mindset, with the ability to define metrics and report results objectively, including limitations
• Excellent written and verbal communication skills; able to work independently and collaborate across analytical, computational and IT functions

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 $24 to $33 commensurate with the level of degree program in which an applicant is actively enrolled. We continuously review market data and may adjust salary ranges as needed in the future. Benefits include medical coverage, paid time off, paid holidays, disability and life insurance benefits, and other company-sponsored benefits. For additional information regarding our benefits and Total Rewards offerings.