Job Information
Massachusetts Institute of Technology Postdoctoral Associate, AgeLab in Cambridge, Massachusetts
Postdoctoral Associate, AgeLab
Job Number: 23643
Functional Area: Research - Engineering
Department: Center for Transportation & Logistics
School Area: Engineering
Employment Type: Full-Time Temporary
Employment Category: Exempt
Visa Sponsorship Available: Yes
Schedule:
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Job Description
POSTDOCTORAL ASSOCIATE, AGELAB, Center for Transportation & Logistics (CTL), to support a broad range of naturalistic driving research efforts. Will collaborate with senior researchers to explore novel data sets and design, and develop new data extraction approaches from telemetry data and video. Responsibilities include designing, building, and performing analytical experiments on naturalistic driving data; reporting on results with an emphasis on developing the foundations of research needed to influence the design and development of vehicle safety systems; leading and contributing to the development of joint publications, participating in conferences, and sharing results with laboratory partners and industry sponsors; and collaborating with the research team on defining research priorities. This position offers an opportunity to work with cutting-edge naturalistic driving data; and enhance societal understanding of driver safety in areas encompassing driver attention (distraction), Advanced Driver Assistance Systems (ADAS), and other higher-level forms of automated driving.
Job Requirements
REQUIRED: Ph.D. in industrial engineering, psychology, physiology, human factors, computer science, public health, or a demonstrably relevant field; record of individual initiative and originality in research; strong analytical skills; and familiarity with statistical software tools such as R or Python. PREFERRED: training, skills, and research interests that complement the research interests of the MIT research team. Candidates with backgrounds and experience in human factors, experimental psychology, data sciences, machine learning, deep learning, or similar areas of expertise are encouraged to apply. Job #23643This is a one‐year appointment, renewable dependent upon performance and funding.1/24/24