The High Energy Physics and the Laser Interferometer Gravitational-wave Observatory groups at the Massachusetts Institute of Technology (MIT) are seeking applicants for postdoctoral research within our groups. The incoming postdoctoral associate will work on the application of machine learning algorithms, heterogeneous computing combining CPUs, GPUs, as well as Field Programmable Gate Arrays (FPGAs) to real-time data acquisition, triggering and physics science analyses. Our groups are collaborating on these aspects as part of an NSF award we received funding for. We are seeking an excellent candidate who can bring 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.
Candidates should have a Ph.D. in physics, astronomy or computer science. Experience with machine learning algorithms is highly preferred. Additionally, experience with GPUs and FPGAs are also highly preferred. Candidates should be familiar with machine learning accelerated approaches and their applications to scientific problems. The candidates 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.
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 1st, 2019. The appointment is initially for one year and renewable annually. In addition to applying online with a curriculum vitae via the MIT careers portal, candidates are asked to arrange for three letters of recommendation to be sent via email to: Philip Harris (email@example.com) and Erik Katsavounidis (firstname.lastname@example.org).
© 2019 American Astronomical Society