Postdoctoral Associate, Kavli Institute for Astrophysics and Space Research

Massachusetts, United States
12 Jan 2021
End of advertisement period
12 Mar 2021
Contract Type
Full Time

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, Kavli Institute for Astrophysics and Space Research, to join the High Energy Physics and Laser Interferometer Gravitational-wave Observatory groups.  Will work on the application of machine learning algorithms and heterogeneous computing combining CPUs, GPUs, and Field Programmable Gate Arrays (FPGAs) to real-time data acquisition, triggering and physics science analyses. The two groups are collaborating on these aspects as part of an NSF award and seek someone who brings modern machine learning strategies combined with heterogeneous computing to the science frontier both at the Compact Muon Solenoid (CMS) detector on the Large Hadron Collider (LHC) and at the LIGO observatory.  Will be part of a team to design and deliver a GPU/FPGA based acceleration system to be used for rapid gravitational wave detection and high-speed processing of CMS data on the LHC. 

Job Requirements

REQUIRED:  a Ph.D. in physics, astronomy, or computer science; familiarity with machine learning accelerated approaches and their applications to scientific problems

PREFERRED:  experience with machine learning algorithms and experience with GPUs and FPGAs.  Job #19066

In addition to applying online via the MIT website, interested candidates should send a curriculum vitae and arrange for three letters of recommendation to be sent via email to Philip Harris ( and Erik Katsavounidis (

The position is available effective immediately and applications will be considered until the position is filled; but to ensure full consideration, candidates should apply by December 1, 2020.

The appointment is initially for one year and renewable annually. 

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