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Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems)
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Harvard University
Cambridge, Massachusetts, United States
(on-site)
Posted 18 days ago
Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems)
Share Print
Harvard University
Cambridge, Massachusetts, United States
(on-site)
Salary
$67,600 - $91,826
Salary - Type
Yearly Salary
Job Function
Other
Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems)

The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Postdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems)
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.

Description

Harvard University



Position
Details
TitlePostdoctoral Fellow in On-Premise Computing for Autonomous Vehicles (Computer Architecture, Machine Learning and Runtime Systems)
SchoolHarvard John A. Paulson School of Engineering and Applied Sciences
Department/AreaElectrical Engineering/Computer Engineering/Computer Science
Position Description

Project


Deep learning plays an essential role in the operation of an autonomous vehicle (AV), allowing for automated detection, prediction, mapping, and planning. During the vehicle's operation, data is obtained through a myriad of sensors in an AV—including RADAR, LIDAR, cameras, and other advanced driver assistance systems (ADAS) sensors. These sensors generate a vast amount of data concurrently, which need real-time processing (latency-bound throughput) for vehicle safety. A crucial challenge meeting this requirement is the simultaneous need for low-power consumption.

The main objective of the project is to develop a complete end-to-end high-performance DNN system for on-premise computing applications—mainly for a SWaP-constrained AV—using hybrid electro-photonic accelerators. We propose to design and prototype a complete electro-photonic computing (EPiC) system (CPUs + accelerators), integrate it with the sensors in AV, and demonstrate its capability to perform perception, mapping, and planning while overcoming the power and performance limitations of CMOS-only computers. As our end goal, we plan to demonstrate a fully autonomous buggy that uses our EPiC system.

This project is a collaboration among Lightmatter, Boston University, and Harvard University. The Lightmatter team is led by Dr. Darius Bunandar, the Boston University team is led by Prof. Ajay Joshi, and the Harvard University team is led by Prof. Vijay Janapa Reddi.

Role


Our team has two postdoctoral researcher openings. The postdoctoral researchers will be jointly supervised by Prof. Joshi at Boston University and Prof. Reddi at Harvard University. The appointment is for one year with an optional second year, subject to performance and availability of funds. The expected start date is January 1, 2022.

Responsibilities

The responsibilities of the postdoctoral researcher include:
  • Work closely with the graduate students at Boston University and Harvard University, and the engineers at Lightmatter to complete the deliverables of the project.
  • Publish research papers in top-tier conferences, and present the work at conferences, other universities, and companies.
  • Participate in developing new research projects and writing grant proposals.
Basic Qualifications
Applicants are expected to have a Ph.D. in EE, CE, or CS (by the start date) with expertise in at least one (or more) of the following areas:

  • Computer Architecture/Systems: Design, modeling, simulation, and/or physical design of heterogeneous system/processor architectures; Silicon-photonic computing architectures; Silicon-photonic network architectures
  • Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing systems
  • Autonomous Vehicles/Systems: Design, integration, and evaluation of AI models for autonomous driving systems; Experience with AV simulators and the AV stack.


Additional Qualifications
Expertise in two or more of the above areas is a plus. Also, hands-on experience with design and prototyping of complete computing systems will be considered a plus.
Special Instructions
Please pay close attention to the following prior to uploading your documents:
  1. CV with a list of your publications.
  2. Cover letter summarizing how your background/experiences makes you a good fit for the project, and your career goals.
  3. Undergraduate and graduate transcripts.

Contact Information
Sarah Gayer
Contact Emailsgayer@g.harvard.edu
Salary Range
$67,600 $91,826
Pay offered to the selected candidate is dependent on factors such as rank, years of experience, training or qualification, field of scholarship, and accomplishments in the field.
Minimum Number of References Required2
Maximum Number of References Allowed5
Keywords
On-Premise Computing
Autonomous Vehicles
Computer Architecture
Machine Learning
Runtime Systems
EEO/Non-Discrimination Commitment Statement

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.

Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.

Supplemental Questions

Required fields are indicated with an asterisk (*).

    Applicant Documents
    Required Documents
    1. Curriculum Vitae
    2. Cover Letter
    3. Transcript
    Optional Documents




      PI278656062



      Job ID: 80575791
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