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Jobs with A3D3
There are research fellowships and employment positions for you to be involved in A3D3
2025-2026 Postbaccalaureate Research Fellows
We are seeking postbaccalaureate research fellows to join our interdisciplinary teams of scientists and engineers to develop and deploy artificial intelligence (AI) to accelerate science discoveries in particle physics, astrophysics, biology, and neuroscience.
The next application deadline is February 16, 2025!
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:
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, 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, 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
Georgia Institute of Technology
Project Description:
Postbacc fellows will work together with mentors to develop accelerated and trustworthy machine learning methods to solve application problems in sciences with irregular data. We recently have focused fast transformer models for geometric deep learning, stable models and out-of-distribution generalization.
Mentors:
Pan Li
Desired Competencies (may be learned on the job):
Coding in python; competency in machine learning and math; technical communication
Location:
Atlanta, GA
Postdoctoral Scholar – ATLAS and A3D3
The Department of Physics at the University of Washington invites applications for a post- doctoral scholar position beginning Summer 2024. The successful candidate will work on the ATLAS experiment at the LHC and A3D3 Institute with Professor Shih-Chieh Hsu, collaborating with the UW Elementary-Particle-Experiment (EPE) group, and will be based at CERN.
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