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Post Doctoral Fellow
Clemson University in College Station, Texas
Date Posted 12/09/2021
Admin-Other Administrative Positions
Employment Type
Application Deadline Open until filled

Post Doctoral Fellow
Clemson University: College of Engineering, Computing and Applied Sciences: Automotive Engineering
Greenville, SC
Open Date

Dec 06, 2021


The postdoctoral fellow will participate in an interdisciplinary, funded research project related to Deep Reinforcement Learning for Cyber-Physical Vehicle Systems operating in unstructured environments within the broader Autonomy Focus Area of Clemson’s VIPR-GS research center (see details below).

This project engages 6 faculty researchers and 6 Ph.D. students from across 4 departments: Automotive Engineering, Mechanical Engineering, Electrical Engineering and Computer Science.

The postdoctoral candidate is expected to provide research-coordination within this larger team and should have strong technical, communication, and project management skills.

Specific duties include: (1) Developing multi-scale reinforcement learning models for perception, localization, planning, and/or control of connected and autonomous cyber-physical vehicles; (2) Verifying and validating models with physical robots and full-sized vehicles, (3) Formalizing tradeoff analyses of a spectrum of data-driven vs physics-informed machine-learning deployments for performance/reliability/robustness, (4) Working with the research-team to understanding the impact of delays and uncertainties, (5) Leading the development of manuscripts and reports, (6) Participating in proposal development, (7) Mentoring graduate and undergraduate students within the research team, and (8) Other duties as assigned.


Required qualifications: PhD degree in engineering, computer-science, or a related field (within the last three years or soon to graduate) with a focus on autonomous systems; strong analytical and problem solving skills; ability to work both independently and collaboratively; experience with supervising students, technicians, and researchers; strong communication skills with examples of technical papers and presentations; documented coding skills.

Differentiating Factors: Experience with frameworks such as ROS, TensorFlow, PyTorch, Mathworks RTW/dSpace; CAE toolchains (e.g. MSC/Hexagon, SIEMENS); general proficiency in design, hands-on prototyping; familiarity with Institutional Review Board (IRB) process; willingness and ability to acquire new skills and knowledge as needed during the project.

Application Instructions

The position is available January 1, 2022 with an initial appointment for one year and possibility for extension for additional years. Candidates should submit (1) a cover letter, (2) a curriculum vitae, (3) 2 sample papers, (4) research statement, (5) portfolio of past research, and (6) list of 3 references with full contact information to Interfolio (http://apply.interfolio.com/99991 ). The review of applications will begin immediately and continue to be accepted until the position is filled.

For inquiries please contact Prof. Venkat Krovi, vkrovi@clemson.edu, Michelin SmartState Chair Professor of Vehicle Automation, Clemson University. Please note that US citizenship/Green Card is not necessarily required, but non-US persons will need to go through an approval process by the sponsoring agency.

Application Process
This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.
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Equal Employment Opportunity Statement

Clemson University is an AA/EEO employer and does not discriminate against any person or group on the basis of age, color, disability, gender, pregnancy, national origin, race, religion, sexual orientation, veteran status or genetic information. Clemson University is building a culturally diverse faculty and staff committed to working in a multicultural environment and encourages applications from minorities and women.

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