Postdoctoral Associate, Machine Learning for Medicine
Massachusetts Institute of Technology (MIT)
May 2, 2018
Research - Laboratory/Non-Laboratory, Staff/Administrative
Working at MIT offers opportunities, an environment, a culture – and benefits – that just aren't found together anywhere else. If you're curious, motivated, want to be part of a unique community, and help shape the future – then take a look at this opportunity.
POSTDOCTORAL ASSOCIATE, Institute for Medical Engineering & Science (IMES), to assume a position in Machine Learning for Medicine, a multidisciplinary research team developing machine learning techniques for medicine, physiological modeling, and treatment decision support. The project offers opportunities to develop/apply novel machine learning and statistical methods to derive actionable insights from physiological signals as well as complex medical data from electronic health records. Duties will include conducting original research, data assembly and analysis, assisting with writing technical manuscripts, publishing in peer-reviewed scientific literature, training technical staff and students, and collaborating on the development of research proposals.
Job Requirements REQUIRED: Ph.D. computer science, machine learning, statistics, or a related field; demonstrated ability to conduct for independent research in advanced machine learning and statistical inference; self-motivation; and outstanding computing and communication skills. Knowledge of and experience in one or more of the following areas would be desirable: deep learning, interpretable models, state space models, dynamical systems, high-dimensional multivariate time series models (longitudinal analysis), causal inference, and reinforcement learning. Knowledge of physiological signal processing would also be desirable. Job #16007
In addition to a curriculum vitae, applicants should submit a short statement of research interest as soon as possible, preferably by May 25, 2018.
Internal Number: 16007
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