Position Open: Time Series Machine Learning

Position Description

The UF Data Studio is partnering with Colgate-Palmolive to develop machine-learning models to predict the chemical properties of new products. The student will build an interface to investigate model features and work with domain scientists to tune specialized features in time series data. We will also work to publish the methods.

Responsibilities

As a machine learning technical contributor, the researcher will join the UF Data Studio and researchers at Colgate-Palmolive. The researcher will train time series models of experimental measurements. We will study several models and assess the performance of each. The researcher will also need to develop an intuitive interface to evaluate performance and communicate with chemists and other domain scientists. The researcher will need to work full-time (20 hr/week). The position is only available in the Fall '24 and Spring '25 with an opportunity for extension.

Qualifications

• Experience building and tuning ML Models.
• Experience with PyTorch and time series models is a significant plus.
• Strong programming, mathematical, and analytical skills.
• Ability to work independently and in a team environment.
• Exceptional written and verbal communication skills.
• Ph.D., Master's, or talented undergraduate students welcomed.

Salary

Graduate students will be paid as a CISE Grad Student. Undergraduate salary will start at $16/hour.

How to apply

Contact: Dr. Grant at cgrant@cise.ufl.edu with the subject line "Ph.D. Position #3"

In the email, directly address each of the qualifications and included above. Use specific examples and of how you satisfy the qualifications. We will begin reviewing applications immediately.

Attach your CV/Resume.