Postdoctoral Fellowship – Machine Learning for Drug Discovery in the Department of Computer Science and Engineering at the University of Connecticut
About University of Connecticut:
The University of Connecticut (UConn) is ranked within the top 20 public universities in the United States and designated as “highest research activity” by the Carnegie Classification of Institutions of Higher Education. UConn has more than 70 focused research centers where faculty, graduate students and undergraduates explore everything from improving human health to enhancing public education and protecting the country’s natural resources. Over the past two decades, UConn and the State of Connecticut have invested heavily in building STEM programs to meet next generation workforce needs. Over $2.8B has supported capital projects to advance UConn’s teaching and research. UConn Technology Park and the new $172M Innovation Partnership Building offer resources that support basic research and technology translation. The primary 4,400-acre campus at Storrs is approximately a half hour’s drive from Hartford and in between Boston and New York City with a bit over an hour drive from each.
The Laboratory of Machine Learning & Health Informatics at UConn (also affiliated with the Connecticut Advanced Computing Center) has a Postdoctoral Fellow position for Machine Learning and its applications in Drug Discovery and System Pharmacology. The Laboratory has produced various novel machine learning methods (as published at NeurIPS, ICML, AAAI etc). We are looking for highly motivated candidates with the background in machine learning and computational chemistry. The candidate would work closely with other computer scientists, chemists, biologists to develop and apply cutting-edge AI approaches for drug discovery.
Responsibilities of these positions include:
Develop novel machine learning algorithms or data science solutions packages for drug discovery and automated chemical synthesis
Prepare research manuscript, scientific presentations and assist in the preparation of research proposals or annual project reports to funding agencies
Support the collaboration with other institutions of the research team
Mentor junior Ph.D. or undergraduate students and help to organize project meetings
Ph.D. in one of the following research areas: Computer Science, Software Engineering, Computational Chemistry, Bioinformatics, Computational Biology or related field
Excellent communication skills and ability to work in a multi-disciplinary teamwork
Either profound understanding of machine learning techniques, such as deep learning, Bayesian optimization, knowledge base modeling, natural language processing methods (e.g., Transformers), or demonstration of prior experience with applying modern machine learning techniques to drug design, chemical property or reaction prediction, bioinformatics and system pharmacology.
Fluency in programming languages, particularly Python and C/C++, and various deep learning frameworks, such as PyTorch, Keras, Tensorflow
Experience with high performance computing and relational databases will be a plus;
To apply, please send your resume, sample publications to Prof. Jinbo Bi at email@example.com, an endowed chair professor at the Department of Computer Science. A review of applications will be on a rolling basis and will continue until all positions are filled.
Tagged as: Chemistry, Computer Science, Life Sciences