Postdoctoral Fellowship – Machine Learning & Health Analytics in the Department of Computer Science and Engineering at the University of Connecticut
About University of Connecticut:
The University of Connecticut (UConn) was founded in 1881, and is ranked within the Top 20 Public Universities and within Top 60 National Universities in the United States and is amongst the elite institutions designated as “highest research activity” by the Carnegie Classification of Institutions of Higher Education. UConn is fully accredited by the New England Association of Schools and Colleges (NEASC) and is a research-intensive university, a prestigious designation shared by only the nation’s top higher education institutions, with 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. In 2013, the State committed an additional $1.7B through Next Generation Connecticut to further support infrastructure development and the hiring of 200 new faculty members. In addition, UConn Technology Park and the new $172M Innovation Partnership Building offer resources that support basic research and technology translation. The primary 4,400-acre (17.8 km2) campus at Storrs is approximately a half hour’s drive from Hartford and in between Boston and New York City with an hour and half drive from each.
The Laboratory of Machine Learning & Health Informatics at UConn has multiple Postdoctoral Fellow positions in the research area of Machine Learning and its applications in Smart Health, and Drug Discovery, and Bioinformatics. These positions will be funded by multiple federal funding agencies, including NSF, NIH and Department of Veteran Affairs. These projects will involve collaboration with research teams distributed across several US universities, e.g., Yale University and University of Pennsylvania, and international hospitals. The responsibilities of these positions include:
* Development, implementation, evaluation and reporting of machine learning models, algorithms, and software packages.
* Contributing to research manuscript preparation and scientific presentations
* Assisting in the preparation of annual reports describing the progress of the research to funding agencies.
* Supporting the collaboration with other institutions of the research team.
* Presenting at site visits and other project team meetings including teleconference and video conference-based meetings.
* Mentoring junior Ph.D. students for specific projects and helping organize project meetings.
* Ph.D. in Computer Science or Mathematics, or Statistics by the time of appointment.
* Strong background in machine learning, statistical inference, mathematical programming, and optimization techniques, as demonstrated by publications and other professional activities, appropriate to the number of years in the field.
* Expertise with programming languages appropriate to the specific field of study and building/maintaining software systems.
* Expertise with parallel and/or distributed computing will be a plus.
* Experience with real-time streaming data analytics and parallel computing will be a plus.
* The annual salary is competitive and dependent upon experience.
* The expected start date is flexible, and the earliest appointment is expected to begin on September 1st, 2018 for two years and can be renewable on a yearly basis and contingent upon funding availability.
To apply, please send your resume, sample publications, and names and contact information of three professional references to Prof. Jinbo Bi at firstname.lastname@example.org. Review of applications will be on a rolling basis and will continue until all positions are filled.