Several NIH-funded data scientist positions are available in Prof. Gaurav Pandey’s lab (gpandeylab.org/) at the Icahn School of Medicine at Mount Sinai in New York City. The overall project for these positions is the design and implementation of novel machine/deep learning algorithms to predict disease phenotypes from a variety and large amounts of clinical data, such as medical images, EEG and audio recordings, omic profiles, structured EHR data and clinical notes. The responsibilities of these positions include preparing robust implementation of these algorithms in a big data environment, especially large high-performance computing clusters. This work will be conducted in close collaboration with several prominent collaborators at Mount Sinai and beyond.
The Pandey lab focuses broadly on developing and applying computational methods to build network and predictive models of complex biological processes and diseases from large biomedical data sets. Lab members routinely analyze large biomedical data sets to build accurate models of biological processes and complex diseases, such as cancer, type-2 diabetes and Alzheimer's disease. Being positioned within a prominent medical center such as Mount Sinai makes it possible to bring the predictions and therapeutic discoveries from these models to patients' bedside, thus placing the lab in a unique position.
The selected candidates will be able to contribute to the ongoing projects in the lab, as well as define their own projects.
Candidates should have a Masters or PhD-level degree in any computationally-oriented field and should have a solid background in programming and computational techniques. They should have a strong interest in participating in research in data science and computational biomedicine.
To apply, send a CV, an experience statement and three reference letters to email@example.com.