What are the responsibilities and job description for the data science postdoc position at Worcester Polytechnic Institute?
Company Description Worcester Polytechnic Institute (WPI) is a leading technological university known for its exceptional students, world-class faculty, and state-of-the-art research facilities. The institution fosters a collaborative, innovative environment where research and teaching intersect to address real-world challenges. WPI supports ambitious scholars who seek rigorous intellectual engagement and opportunities to make a meaningful impact. The university’s culture emphasizes interdisciplinary work, professional growth, and mentorship, helping community members advance their careers while contributing to society.
Role Description The Data Science Postdoc is a full-time, on-site role based in Worcester, MA. The postdoctoral researcher will design and conduct data-driven research projects, including developing and validating analytical methods, building models, and interpreting complex datasets. Day-to-day activities include collaborating with faculty and research teams, performing quantitative analysis, preparing manuscripts, and presenting findings at seminars and conferences. The role may involve supporting laboratory-based data collection, integrating results into data science workflows, and contributing to proposals and reports. The postdoc may also assist with teaching-related activities such as mentoring students, guiding project work, and contributing to data science and related coursework.
Qualifications
- Strong research skills in data-intensive domains, including experience designing studies and working with interdisciplinary teams.
- Proficiency in data analysis, such as statistical modeling, machine learning, computational methods, and data visualization.
- Relevant laboratory skills for data collection, experimental setup, and accurate documentation of procedures and results.
- Background in physics or a closely related quantitative field, with the ability to apply theoretical and computational tools to data science problems.
- Teaching and mentoring abilities, including supporting student learning, supervising projects, and communicating complex concepts clearly.
- Doctoral degree (PhD) in data science, physics, engineering, computer science, statistics, or a related discipline.
- Experience with programming languages and tools commonly used in data science (e.g., Python, R, MATLAB, SQL, or similar) and version control systems.
- Strong written and oral communication skills, ability to present research to diverse audiences, and commitment to inclusive, collaborative work practices.