The board
- Hours
- Full time
- Where
- St. Paul, Minnesota, USA
- Posted
- Sep 8
As the largest pureplay adhesives company in the world, H.B. Fuller’s (NYSE: FUL) innovative, functional coatings, adhesives and sealants enhance the quality, safety and performance of products people use every day. Founded in 1887, with 2025 revenue of $3.5 billion, our mission to Connect What Matters is brought to life by more than 7,100 global team members who collaborate with customers across more than 30 market segments in 150 countries to develop highly specified solutions that enable customers to bring world-changing innovations to their end markets. Learn more at www.hbfuller.com.
What you can expect from H.B. Fuller’s Internship Program:
You’ll be joining a cohort of talented students from a variety of schools across the U.S.
What you'd do
- 12-week paid program beginning the end of May to mid-August to gain insight and knowledge in your field.
- Interactive orientation and events with skilled professionals in your field, including managers, directors, and CEO.
- Multiple networking, volunteer and fun events – both virtual and in-person.
- Impactful projects that make a difference internally and externally for H.B. Fuller.
- End of summer final presentation to showcase your career development with support from managers and peers.
- Collaborate with R&D scientists to collect, curate, and structure experimental data for machine learning applications.
- Develop and validate interpretable machine learning models to predict critical material and formulation properties.
- Analyze model outputs to identify meaningful structure-property relationships and generate scientific insights.
- Apply machine learning techniques to propose novel formulations and candidate materials meeting targeted performance requirements.
- Develop workflows for data preprocessing, feature engineering, model training, and model evaluation.
What they want
- Currently pursuing a Bachelor's degree in Materials Science & Engineering, Chemistry, Chemical Engineering, Polymer Science, or a related scientific discipline.
- Demonstrated proficiency in Python and common scientific computing libraries, including Pandas, NumPy, Scikit-learn, and PyTorch or TensorFlow.
- Strong understanding of machine learning fundamentals, including model development, validation, and interpretation.
- Strong theoretical understanding of chemistry, polymer science, or materials science principles.
- Excellent written and verbal communication skills and the ability to effectively collaborate with multidisciplinary scientific teams.
- Starts
- 2026-09-08