Senior Computational Scientist

E Ink is the originator, pioneer, and commercial leader in ePaper technology. The Billerica Research & Development team is thriving and growing as we help develop products that are changing how people access information every day. We are seeking qualified candidates who are self-driven, looking to advance their career and become a high-impact player on a team.

Based on technology from MIT’s Media Lab, E Ink has transformed and defined the eReader market. Its Electrophoretic Display products make it the worldwide leader for ePaper. The Company’s corporate philosophy aims to deliver revolutionary products, user experiences and environmental benefits through advanced technology development.

Our diversity of people, backgrounds, experiences, thoughts and perspectives is fostered to create an inclusive work environment.

Our culture is built on value commitments to innovation, quality, results, integrity, community, people, and collaboration that fosters a strong employee engagement, teamwork, safety and wellness.

We offer a competitive/generous benefits package that fits the needs of our employees. It includes health, dental, vision, wellness programs, employee discounts, 401k matches, ongoing development, advancement opportunities and more. This position is also eligible for our bonus program.

Computational Scientist to support development efforts toward improved electrophoretic displays. In this role you will use deep learning, data science, computational methods and natural sciences to design, improve and evaluate models of our displays and develop algorithms and tools in support of this effort. You will work closely with our materials scientists to incorporate novel experimental results into your models which in turn will inform the materials scientists’ work.

Be part of a larger team and support it in collaboration with our materials science platform engineer. This will take the shape of developing tools and automated processes that enable the team to make greater use of your models and results.

As part of our innovative team, your work will be instrumental in enabling rapid screening pipelines that enable collection of large datasets, with the goal of operating them at scale and increasing their throughput by >100x over the next year.

The successful candidate will have strong analytical and communication skills, and a record of driving toward pragmatic solutions to industrial problems.

• Develop, improve, and evaluate models pertaining to the fundamental dynamics of electrophoretic displays, and use them to drive inverse design efforts toward better performing displays
• Work closely with our materials scientists to shape experiments, contribute to their analysis, and incorporate the results into your models
• Design and maintain reproducible pipelines that process experimental data as well as train and evaluate machine learning models
• Conduct inverse-design campaigns (Bayesian optimization, diffusion models, genetic algorithms, etc.) to iteratively recommend new formulations and coordinate lab validation
• Support your wider team with tools and algorithms that make your models and results easily accessible and usable
• Dive deep into fundamental ink dynamics and chemistries to discover key insights related to material properties and chemical design
• Invent and document relevant intellectual property and present findings to broad audiences
• Champion best practices in data quality and experiment lineage across the organization
• Act as the glue between collaborators working at the interface of soft-matter science and machine learning

• Minimum of a Ph.D. (or exceptional M.S. plus 4 years' experience) in Materials Science, Chemistry, Data Science, Physics, Applied Math, or similar major. Outstanding candidates of any educational background will be considered
• 3-5 years of experience in a research role with a proven track record of innovative solutions
• Proficiency in Python or other scientific programming tools
• Strong problem-solving skills and the ability to work collaboratively in a multidisciplinary team
• Ability and openness to learn new tools and techniques and share…