JOB DESCRIPTION: Helps design and conduct research within a specified field while receiving advanced training from a designated Principal Investigator to enhance professional skills and research independence needed for pursuit of a career. The specific area of research in which the trainee is mentored is determined by the department and laboratory of the Postdoc. Designs and evaluates experiments. Develops new ideas that promote current research. Prepares and publishes scientific manuscripts under the direction of the Principal Investigator. May be responsible for operation of specific equipment. May teach techniques to others, train, and supervise research staff. Positions are temporary appointments as a research trainee. The initial appointment is for one year, renewal expected if progress is satisfactory and funds are available. Appointments cannot exceed five years.

Program Highlights:

Analysis of high-dimensional temporal data ubiquitously arising from practices such as patient monitoring, health tracking, and symptom management is challenging but also rewarding in terms of both meeting unmet needs in healthcare and advancing the state of the art in AI/ML algorithms.

Major applications being pursued by the hiring lab include multimodality brain monitoring of patients with acute brain injuries in neurocritical care units, integration of data from electronic health record with physiological data to develop predictive models, modeling/analysis of invasive neurophysiological signals from patients with acute brain injury, Parkinsons disease, and epilepsy, and analysis of data from wearable devices to detect cardiovascular and neurological conditions. Data encountered in various projects include physiological signals (ECG, EEG, ECoG, blood flow velocity, blood pressure, and intracranial pressure), time series data from wearable sensors, clinical data (including clinical notes) from electronic health record systems etc. We pursue this diverse set of applications by relying on the core expertise in algorithm and software development and a close collaboration with various domain experts across multiple institutions and disciplines.

Qualified candidates should have a PhD in at least one of the following fields: biomedical engineering, biomedical informatics, health sciences (nursing, cardiology, health service research, neurology), applied statistics/math, electrical/computer engineering.

Candidates also need to have a publication track record showing research experiences that developed or applied at least one of the following techniques to solve a problem related to the broad application areas as listed above: signal processing/time series analysis, machine learning, deep learning, mathematical modeling, system identification, optimization, digital/mobile health, natural language processing, and data visualization.