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There are research fellowships and employment positions for you to be involved in A3D3. This page summarizes the latest opportunities.

Administration

Postdocs

Postbaccalaureate Research Fellows

Participating sites and possible projects for 2022-2023 (Apply through Academic Jobs Online):
  • Purdue University
    • Project Description: Postbacc fellows will work together with mentors to develop advanced machine learning models, graph neural networks in particular, to solve application problems in high-energy physics and neuroscience.
    • Mentors: Pan Li, Mia Liu, Maria Makin
    • Desired Competencies (may be learned on the job): Coding in python; machine learning; some background knowledge in either higher energy physics or neuroscience; technical communication
    • Location: West Lafayette, IN
  • UC San Diego
    • Project Description: Postbacc fellows will work together with mentors to develop the python-based hls4ml and other AI-hardware codesigns software tools for implementing, compressing, and quantizing neural network algorithms on FPGAs with sub-microsecond inference latency. Fellows will also apply these techniques to collider physics including regression and classification tasks related to jets and missing transverse energy as well as general anomaly detection in the CMS Phase-2 Level-1 trigger.
    • Mentors: Javier Duarte
    • Desired Competencies (may be learned on the job): Coding in python; machine learning; FPGA firmware development; high-level synthesis; collider physics; trigger; technical communication
    • Location: La Jolla, CA
  • University of Minnesota
    • Project Description: Postbacc fellows will work together with mentors to develop machine learning applications applied to both gravitational-wave detector such as the Laser Interferometer Gravitational-wave Observatory and optical telescope data such as that from the Zwicky Transient Facility to detect both gravitational waves and their optical counterparts.
    • Mentors: Michael Coughlin
    • Desired Competencies (may be learned on the job): Coding in python (and javascript); machine learning; databases; time-domain astronomy; technical communication
    • Location: Minneapolis, MN
  • University of Illinois at Urbana-Champaign
    • Project Description: Postbacc fellows will work together with mentors to develop fast reconstruction methods and applications based on machine learning to improve real-time data selection for event triggering in high-energy physics and multi-messenger astrophysics experiments. Successful candidates will have the opportunity to collaborate with the Illinois interdisciplinary centers Illinois Center for Advanced Studies of the Universe and Center for Artificial Intelligence Innovation in their research.
    • Mentors: Mark Neubauer and Deming Chen
    • Desired Competencies (may be learned on the job): Coding in python; machine learning; ; FPGA firmware development; high-level synthesis; particle physics; detector triggering; technical communication
    • Location: Champaign-Urbana, IL
  • Massachusetts Institute of Technology
    • Project Description: Postbacc fellows will work together with mentors to develop deep learning algorithms applied to either gravitational-wave detector such as the Laser Interferometer Gravitational-wave Observatory or the Large Hadron Collider to discover new physics events. Additionally students, have the possibility to explore optimized and create their own deep learning architectures.
    • Mentors: Philip Harris Erik Katsavounidis Song Han
    • Desired Competencies (may be learned on the job): Coding in python; machine learning; time-domain astronomy/ Paritcle Physics; technical communication; FPGA programming
    • Location: Boston, MA
  • Duke University
    • Project Description: Postbacc fellows will work together with mentors to develop deep learning algorithms applied to neutrino experiments, with collaborations including the Deep Underground Neutrino Experiment, COHERENT and SNEWS.
    • Mentors: Kate Scholberg
    • Desired Competencies (may be learned on the job): Coding in python; machine learning; time-domain astronomy/ particle physics; technical communication; FPGA programming
    • Location: Durham, NC
  • University of Washington
    • Project Description: Postbacc fellows will work together with mentors to develop deep learning algorithm to i) improve event reconstruction and anomaly detection for high-energy physics trigger system, and/or ii) accelerate processing, organizing, and analyzing massive neural datasets in real time. Successful candidates will have the opportunity to collaborate with the EPE, ACME Lab, CNC, and Neuro AI Lab in their research.
    • Mentors: Scott Hauck, Shih-Chieh Hsu , Amy Orsborn and Eli Shlizerman
    • Desired Competencies (may be learned on the job): Coding in python; machine learning; FPGA firmware development; high-level synthesis; particle physics; neuroscience; technical communication
    • Location: Seattle, WA