I have an immediate opening for a post-doctoral fellow to engage in a federally-funded multi-year project in biomedical deep learning. My research group at Drexel University focuses on developing state-of-the art deep learning-based algorithms and applying them to a wide range of problems. Ongoing projects are:

• Design of novel and application of existing cutting-edge natural language processing (NLP) models (e.g. Transformer, BERT, GPT-2, XLNet) for biomedical information retrieval and text summarization. This is an unprecedented opportunity to harness unstructured information from millions of documents, use this information to guide generic drug product development.

• Development of novel and application of existing deep generative models (e.g. GANs, VAEs) to explain the high-dimensional structure and time course of neural population activity. The focus is on the extraction of low-dimensional temporal patterns in high-dimensional spiking and local field potentials datasets in visual attention and working memory tasks, and the development of new tools for causal inference (e.g. copula Granger-causality).

The ideal candidate should have, or be about to receive, a Ph.D. in a relevant discipline with substantial computational experience (especially in deep learning/NLP). Programming skills in Python and/or Julia are essential. Knowledge of state-of-the-art NLP/text mining methods and/or deep learning frameworks (e.g. TensorFlow, PyTorch) is advantageous but not required.

Interested individuals should email a curriculum vitae and a brief statement of research interests to Dr. Hualou Liang at hualou.liang@drexel.edu.

Hualou Liang, PhD

Professor

School of Biomedical Engineering

Drexel University

3141 Chestnut Street

Philadelphia, PA 19104

Tel: (215) 571-3706

Fax: (215) 895-4983

hualou.liang@drexel.edu

http://www.biomed.drexel.edu/labs/liang/

Mailing address:

Monell Building

3508 Market Street

Suite 100

Philadelphia, PA 19104