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Undergraduate Research Opportunities at Argonne National Laboratory

I am a researcher at Argonne and we have research opportunities for undergraduates.  Nominally, these start in the summer and can continue as part-time jobs during the school year.

Interested students may send their resume to Antonino Miceli, amiceli@anl.gov and they will assist with the application process.

Undergraduate Research Opportunities at Argonne National Laboratory in
Microelectronics, Computing and Detectors


In the almost 25 years since the Advanced Photon Source (APS, https://www.aps.anl.gov), a U.S.
Department of Energy (DOE) Office of Science User Facility, first opened at DOE’s Argonne
National Laboratory, it has played an essential role in some of the most pivotal discoveries and
advancements in science. From chemistry to materials science to COVID-19 research, the APS is
one of the most productive X-ray light sources in the world. An upgrade will make it a global
leader among the next generation of light sources, opening new frontiers in science. Detectors are
an integral part of this scientific discovery. From Wilhelm Röntgen's barium platinocyanide screen
to Georges Charpak's multiwire proportional chamber, detectors are what grant scientists the
ability to see far beyond human limits.
We have multiple paid openings for undergraduate students on various research projects related to
detectors. These include: 1.) digital circuit design and verification for on-chip pixel detector
computing using state-of-the-art microelectronics technologies, 2.) data intensive compute
accelerators for very high network bandwidth, line-rate encryption, compression, streaming data
processing, all offloaded from CPUs, 3.) quantum sensors for X-ray science. The positions will
start in the summer 2023 (potentially sooner) and can be on-site or remote or hybrid. There will
be opportunities to continue working with us during the school year. Project can evolve into senior
thesis projects and there are opportunities to published in peer-reviewed journals. For more
information, please contact Antonino Miceli (amiceli@anl.gov).


Microelectronics - Digital ASIC Design and Verification
Integrated circuits are at the core of our modern world. Integrated circuits are the core of smart
phones and cameras, the internet-of-things, computers, cloud data centers and a new wave of
artificial intelligence processors. What has enabled the proliferation of integrated circuits beyond
computers (i.e., CPUs) is the “pure-play” semiconductor foundry business model, where even
small-scale companies can develop designs that are then fabricated using billion-dollar
semiconductor fabrication facilities. This resulted in a new opportunity for fabless semiconductor
companies to emerge which focus only on integrated circuit design: these companies include giants
like Apple, Nvidia, Qualcomm and Xilinx, as well as startups like Groq, Graphcore, SambaNova
and Cerebras. The academic research community is fortunate to have access to these foundries
which facilitate cost-effective prototyping small designs and full-scale fabrications at relatively
advanced technology nodes. Modern pixel detectors are built on application-specific integrated
circuits (ASICs) fabricated at commercial semiconductor foundries. The general trend of making
larger and faster detectors is imposing a huge burden on data storage, and more importantly, on
data streaming. Thankfully, with the use of more advanced technology, greater digital functionality
from the computing domains can be integrated directly into the detector silicon. Among these
functionalities, hardware-based streaming compression is finding its way into the modern
computing and networking ecosystem.
Reference: “A lightweight, user-configurable detector ASIC digital architecture with on-chip data
compression for MHz X-ray coherent diffraction imaging,” S. Strempfer*, T. Zhou, K. Yoshii, M.
Hammer, A. Babu, D. Bycul*, J. Weizeorick, M. J. Cherukara, and A. Miceli, Journal of
Instrumentation, 17, P10042 (2022). https://doi.org/10.1088/1748-0221/17/10/P10042 
(* undergraduate student)


Data intensive compute accelerators
The increased scientific data rate expected to be produced by larger, faster detectors around the
APS synchrotron, and APS-U feature beamlines in particular, presents a significant challenge to
our existing data movement, storage and compute infrastructure. Scientists have increasingly
turned to artificial intelligence (AI) and machine learning (ML) to analyze data. AI/MLaccelerated
workflows have been shown not only to be fast enough to keep up with experiments,
but also to overcome experimental restrictions of conventional methods. We are using hardware
compute accelerators designed to greatly increase beamline data processing and transfer speeds to
address this challenge. The class of hardware designed to offload computation from the CPU has
greatly expanded in diversity and computational power in the last few years. Add-on cards now
exist which can compress or encrypt network traffic at the line rate and transparently to the host
system, and massively parallel graphics processing units (GPUs) have achieved order-ofmagnitude
speedups in machine learning inference and similar tasks. The APS-U project and the
consequent increased scientific data rates provide the motivation and the opportunity to take
advantage of these advances. Significant work is required to identify and integrate this new
hardware into a data pipeline that aligns and meets the needs of the overall APS computing
strategy. In some cases, software development to port existing algorithms or machine learning
models to specific SDKs and hardware architectures is also needed to take full advantage of
compute accelerator technology.
Reference: “Deep learning at the edge enables real-time streaming ptychographic imaging,” A.V.
Babu, T. Zhou, S. Kandel, T. Bicer, Z. Liu, W. Judge, D.J. Ching, Y. Jiang, S. Veseli, S. Henke,
R. Chard, Y. Yao, E. Sirazitdinova, G. Gupta, M. V. Holt, I.T. Foster, A. Miceli, M.J. Cherukara,
https://arxiv.org/abs/2209.09408


Quantum Sensors for X-ray Science
Superconducting detectors make use of quantum behavior to achieve unprecedented energy
resolution and sensitivity to X-ray photons. The APS Detectors group designs, fabricates, tests,
and deploys superconducting sensor arrays and instruments for use in a variety of X-ray science
applications around the facility, in particular with a prototype Transition-Edge Sensor array
instrument at the detector & optics testing beamline 1-BM-C. New capabilities are being
developed in clean room fabrication using photolithography, thin film deposition and
micromachining and in measuring the low-temperature material properties of the micrometer-scale
structures used. Testing fabricated devices in purpose-built cryostats (50mK) involves a
combination of analog, digital and radio-frequency electronics. Operating the complete instrument
at a beamline requires both an understanding of how each pixel of the detector array operates as
well as the X-ray science application, typically spectroscopy or X-ray inelastic scattering. Software
solutions in Python and C/C++ perform instrument operation and data analysis. Integration with
APS-wide beamline control systems and data analysis packages such as EPICS and XRF-Maps is
ongoing.


Reference: “Devices for Thermal Conductivity Measurements of Electroplated Bi for X-ray TES
Absorbers,” O. Quaranta, L.M Gades, C. Xue*, R. Divan, C.S. Miller, U.M Patel, T. Guruswamy,
A. Miceli, Journal of Low Temperature Physics (2022) , https://doi.org/10.1007/s10909-022-
02876-9 (* undergraduate student)

Last Updated: Nov 30, 2022 9:23 AM

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