Log In
Sign Up
PhD Student
PhD in biomedical data science and computational disease biology Full-time NEW
PhD in biomedical data science and computational disease biology
PhD student positions now available for 2025 developing and applying machine learning models for computational disease biology at UMass Lowell, Center for Health Data Science, departments of Biology and Computer Science.
This research sits at the crossroads of computational biology, data science, and epidemiology, and there are a number of possible projects https://rdmelamed.github.io/#projects Recent projects/papers include: discovering drug combinations that may have latent impact on developing cancer; a model for learning how medications impact genes driving disease; drug repurposing by linking shared genetics of rare and common disease. Your ideas for other projects are welcome!
Our work is 100% computational, modeling public and proprietary biomedical genomic and health records data sets. We use R/python machine learning, neural networks, and statistical modeling toolboxes (such as pytorch, stan, network methods) . In addition to state of the art computational infrastructure, we have access to exciting non-public data on health histories of millions of people, including biobank and health records data.
The candidate will be mentored by Dr. Rachel Melamed, an expert in biomedical data science, and co-mentored by Dr. Tingjian Ge, a computer science professor and expert in graph neural network models. Collaborators in public health including those at the nearby Veteran’s Health Administration research site. PhD candidates can choose from programs in computer science, applied biology, or biomedical engineering.
About the lab, center, and university
Our lab has a focus on mentorship and maximizing the potential for each trainee to achieve their career goals in a healthy, motivated, supported environment. Trainees are invited to attend national and international conferences in the field. Lowell is in greater Boston, a hub of biomedical and data intensive research, which is also short drive from the seashore and mountains.