# Broadening the scope of Education, Career and Open Science in HEP

Sudhir Malik1 David DeMuth2 Sijbrand de Jong3 Randal Ruchti4 Savannah Thais5
Guillermo Fidalgo1 Ken Heller6 Mathew Muether7 Minerba Betancourt8 Meenakshi
Narain9 Tiffany R. Lewis10,11 Kyle Cranmer1,2 and Gordon Watts1,3 1Physics
Department, University of Puerto Rico Mayaguez, Mayaguez, PR 00682, USA
2Science Department, Valley City State University, Valley City, ND 58072
3Physics Department, Radboud University, Nijmegen, The Netherlands  4Physics
Department, University of Notre Dame, IN 46556, USA  5Physics Department,
Princeton University, Princeton, NJ 08544, USA  6School of Physics and
Astronomy, Minneapolis, MN 55455, USA  7Department of Mathematics, Statistics
and Physics, Wichita State University, Wichita, KS 67260, USA  8Fermilab, PO
Box 500, Batavia, IL 60510, USA  9Department of Physics, Brown University,
Providence, RI 02912, USA  10NASA Postdoctoral Program Fellow  11Astroparticle
Physics Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771
12Department of Physics, New York University, New York, NY 10003, USA
13Department of Physics, University of Washington, Seattle, WA 98195, USA
<EMAIL_ADDRESS>
###### Abstract

High Energy Particle Physics (HEP) faces challenges over the coming decades
with a need to attract young people to the field and STEM careers, as well as
a need to recognize, promote and sustain those in the field who are making
important contributions to the research effort across the many specialties
needed to deliver the science. On one hand, trends in education and career
opportunities in HEP have been highly selective and generally exclusionary of
participation by underrepresented minority and female students. Missed are a
significant pool of students and faculty at Predominantly Undergraduate
Institutions (PUIs) and Community Colleges (CC) that could be tapped to
increase and strengthen underrepresented participation. On the other hand, a
current mindset in the field is that highly specialized skills such as
software and firmware development and instrumentation development are not
broadly recognized as “physics” work, and thus the perception of what it means
to ‘be a physicist’ must also be challenged. The view of what constitutes
significant contribution to the physics must be reexamined, expanded and
rewarded. Confronting and addressing these issues would encourage an influx of
new workforce into the field, help retain those who are in the field, and
equip those who might seek careers outside of HEP. Despite the challenges,
there are reasons for optimism. The collaborative nature of the HEP community
and the excitement of the science can serve as potentially powerful organizing
mechanisms to confront systemic issues such as these. The PUI and CC faculty
could be invited to participate and contribute meaningfully to HEP along with
their students, who would acquire a variety of skills that prepare them for
STEM careers. Access to a master’s degree in Applied Physics could enable
technological careers in laboratories, accelerator facilities, the private
sector and could open avenues to more advanced degrees including PhDs. The
Open Science tools established by the HEP community can greatly enable such
participation. A major effort in software training has been organized and
underway through IRES-HEP, to address the breadth and critical nature of the
analytical challenges facing HEP over the next two decades. Inside the HEP
community, Grid Computing, Multi-threaded Software, Machine Learning in
physics analysis and the development of new detector technologies have
empowered our ability to quickly process petabytes of data, see patterns in
them, and potentially discover new physics. And such technological and
analytical benefits are generally extendable to other fields including
medicine. Computing, software, detector design, logical thinking, statistical
analyses, simulation, and hardware development skills have made physicists
highly employable within and outside academia. Such skills can also serve as
attractors for students who may not want to pursue a PhD in HEP but use them
as a springboard to other STEM careers. And importantly, an increased pool of
interested and engaged students and faculty can spawn new and as yet
unforeseen opportunities for the field. This paper reviews the challenges and
develops strategies to correct the disparities to help transform the particle
physics field into a stronger and more diverse ecosystem of talent and
expertise, with the expectation of long-lasting scientific and societal
benefits.

##  1 Introduction

Broader participation by diverse demographic and geographic groups is key to
building strength in STEM fields in general, and High Energy Physics (HEP) is
no exception. A recent report from the National Science Board Vision 2030 [1]
urges that faster progress in increasing diversity is needed to reduce the
significant talent gap in the United States (U.S.). It also indicates that
foreign-born individuals are significant contributors to U.S. Science and
Engineering. The data shows that a global science and engineering enterprise
is growing faster than before, while the U.S. share of scientific discovery is
dropping. The silver lining is that the U.S. has a significant lead in
fundamental research, and we must innovate and embrace ways to be more
inclusive and diverse to maintain our global leadership. For U.S. HEP to stay
competitive and evolve stronger, we must address these issues as part of the
planning process for the next decade so that an influx of new workforce in the
field can be encouraged, retaining those who are in the field and as well
equip them with a skills to find careers both within and outside HEP.

The current trend of education, diversity, gender and career opportunities in
HEP [2] is highly selective, and generally exclusionary of participation by
underrepresented minority and female students. To address this issue,
meaningful opportunities for broader participation are required at different
levels. While a proposed Master’s Degree in Applied Physics could enable a
technological career in laboratories, accelerator facilities, private sector,
or possibly a PhD degree, it can also attract students from less favored
communities who may wish to transition to a career with a Masters degree.

At Ph.D. and post-doctoral level, a vast majority of researchers who choose to
stay in academia are hired as teaching faculty at Predominantly Undergraduate
Institutions (PUIs) [3, 4] and Community Colleges (CCs). Moreover, these
institutions host a vast majority of students from underrepresented groups.
The faculty of these institutions, despite their talents, are at disadvantage
when it comes to continuity in research that requires commitment of both time
and resources. Typically, higher teaching loads, lack of informed guidance,and
lack of collaborative opportunities diminish their chances for being
competitive for research funding.

The strength of the particle physics community lies in its openness,
diversity, and access to some of the best creative talent worldwide. This
strength has resulted in the advancement of human knowledge that is leading to
a detailed understanding of the inner workings of the universe. Engaging
undergraduate institutions and their faculty and students in this front-line
research enterprise would both enrich and strengthen the workforce and the
field.

With the advent of tools for Open Science, we are poised for an even greater
and more significant role, and in a more inclusive way. For example, CERN Open
Data [5] is being harnessed to connect discovery science with the public
through outreach activities, techniques such as Machine Learning, and much
more. Development of state-of-the-art particle sensors often find applications
outside of particle physics, e.g. in medical imaging, material diagnostics,
etc. Small scale development and application research is well in reach of
smaller research groups with limited resources, if they can be teamed up with
larger scale HEP collaborations. The software training in the HEP community is
transforming the preparation of our next generation of problem solvers by
reaching students beyond HEP.

We must strengthen existing successful methodologies, many of which have been
created and developed by the U.S. HEP community, and explore new ways of
transferring HEP resources, talent, and data into an Open Science paradigm. By
doing so we propel our field forward, and garner the interest and support of
general public through the next phase of scientific discoveries.
Simultaneously, we must prepare HEP Ph.D. students and postdocs for careers
inside or outside academia.

We recognize that advancements and discoveries in physics have become a huge
enterprise necessitating advances in computing, software, AI, Machine Learning
and detector technologies in order to develop, design, build and operate
experiments. And these consume a significant fraction of time of physicists.
This means that our perception of what it means to ‘be a physicist’ and what
work is considered a contribution to the physics must evolve and expand. In
the following sections we discuss several proposals to address and mitigate
the aforementioned challenges.

##  2 Assessing the needs of Particle Physics

The Standard Model of particle physics provides an an impressive description
of much of observed particle physics. Nevertheless, it has significant
shortcomings and cannot be the ultimate theory of nature at the fundamental
scale. Theoretical particle physics provides a plethora of extensions and
modifications of the Standard Model, many of which predict new physics
phenomena for which there are either minimal or no observational motivations
at present. Further groundbreaking experimental programs will be required to
make further scientific discoveries. These can be forged by going to higher
energy, measuring more precisely or by performing measurements with new
techniques. It is not unreasonable to assume that new discoveries will
incorporate all three of these attributes.

In all cases the progress will be technologically driven, in accelerator
technology, in sensor technology, or in data treatment and analysis
technology. Strong injection of technological know-how is therefore a
requirement for progress. Much of the technological; progress does not
necessarily require extensive particle physics knowledge. Rather it does
require a deep understanding of technology and the ability to innovate and
create new technology.

Unlocking the technological work-force needed for future particle physics
research requires recruiting talent outside the normal particle physics
oriented study and career paths. There is potentially large pool of students
and faculties at PUIs and CCs that can be tapped to increase such
participation. The faculty could contribute to HEP along with students who
would acquire various skills that prepares them for STEM careers.

That this potential is not well accessed at the moment is due to resource
limitations in these faculties, in terms of research time and equipment and
travel budgets. There is also little awareness of the potential for
significant contribution from these faculties with the faculties themselves
and with the current main players in HEP, the R1 [3] universities and research
institutions.

In sections below, suggestions are made to implement programs to unlock the
potential for technical education and research connected to experimental
particle physics. While such a programs would contribute to the development of
new workforce to meet the technical challenges of experimental particle
physics, they would also contribute to making the HEP community more diverse
and offer new opportunities for participation from those underrepresented in
STEM. The next two decades of the Snowmass2021 vision can afford an
opportunity to review the challenges and develop strategies to correct the
disparities and transform the particle physics field into a stronger and more
diverse ecosystem of talent, expertise and public-minded support. Working
together across the various groups of the Community Engagement Frontier and in
consort with the scientific, technical and computation frontiers of the
Snowmass2021 Community Self-study, the community can develop an understanding
and project the person-power needs of the field in terms of students,
physicists, and technical, analytical, and managerial eperts on an annual
basis – and in parallel – project the societal benefits that could be acquired
through this process.

Among the facets of this proposed study:

  * •

Needs Assessment of the Community: Work with the various research and
technical frontiers to develop projections of their person-power and
educational needs on an annual basis over the next two decades.

  * •

Needs Assessment of the Education Process: Review of teaching at all levels –
particularly transition points between education levels – where “transmission
coefficients” of students are low and develop ideas to improve these
circumstances. Understanding these are particularly important to increasing
the participation of underrepresented groups in the field.

  * •

Model Development to Guide Community Planning: Engage with AIP and APS who
follow the education process of younger students upward through schools to
develop statistical models of what currently is the situation and how it might
be improved, not only to the benefit of particle physics, but also the broader
STEM community.

##  3 Faculty Collaboration across Academia

The field of Particle Physics has successfully brought many young researchers
through the post-doctoral ranks, at which time these individuals are then
searching for more permanent positions in academia, National Laboratories, and
in the private sector. In the domain of academia, many individuals may
consider opportunities at Carnegie classified R1 universities, other
institutions including undergraduate-serving colleges and universities, as
well as community colleges.

For those seeking what are typically teaching-rich positions, the potential
exists for these persons to attract a broader geographic and demographic base
of students to the particle physics field which affords the possibility of
strengthening the participation of underrepresented groups in the particle
physics research program. Engaging those teaching at undergraduate
institutions in front-line particle physics research will strengthen our
academic workforce, and in turn inspire their students.

Recommendations:

  * •

Conduct an analysis to assess the needs of faculty at undergraduate
institutions in order for them to be successful in developing vibrant research
programs, whilst maintaining a significant teaching load characteristic of
such institutions.

  * •

Survey institutional collaborations of PUI and CC faculty with R1 and
laboratory groups that have proven successful so far, to assess lessons
learned.

  * •

Conduct a study of new models of collaboration or cooperation that would allow
PUI/CC faculty and their students to collaborate in demonstrably effective
ways in experiments, and for faculty to be effective leader rather than
regarded as secondary.

  * •

Conduct a survey of R1 institutions and research laboratory physicists who
might share an interest in collaborating with PUI and CC faculty.

  * •

Identify and inventory past and present activities by PUI and CC faculty
engaged in HEP or related activities such as experiment design, construction,
installation, and maintenance.

##  4 New Masters Degree in Applied Physics

A Master’s Degree in Applied Physics is proposed here with the aim of
providing an advanced degree beyond bachelors level that could open meaningful
career paths for students into technological careers in laboratories or the
private sector; additionally such a degree could serve as a springboard for
those who find that a PhD degree is possible. This would provide a meaningful
opportunity for participation by underrepresented groups and enrich and
broaden participation in STEM careers.

Recommendations:

  * •

Conduct a needs analysis to assess the value and chances of success of such a
program.

  * •

Compare such a program with current models of Masters Degrees in engineering
and MBA degrees.

  * •

Conduct an assessment of private sector buy in and support for such a degree
opportunity for current students and for their employees seeking career
improvement.

  * •

Assess the effectiveness of such a degree to provide training opportunities
for those seeking technical careers at laboratories in our field or elsewhere
or perhaps medical fields.

  * •

Identify the curriculum for such degree(s) and whether they could be made
available nationwide through shared curriculum.

  * •

Assess university, PUI and CC buy in and participation in such a program.

##  5 Training the HEP community

Software, computing, hardware and analysis skills are an integral part of the
toolkit of successful HEP experimentalists, and maximizing the science from
the investments in current and future HEP projects relies critically on it.
This is also a skill set that is readily transferable in case of non-HEP
career evolution of people trained in HEP. For example, software training is
now key in many research fields, but most users learn software skills only
after joining a research program. Individual universities do not uniformly
provide such training to students prior to their beginning their Ph.D.
research. HEP Computing and hardware skills at university level are even more
rare given significant costs and time investments. In addition, domain-
specific aspects add challenges to the learning process. Embarking on a HEP-
specific training could still involve experiment-specific environment
challenges. Figure 1 shows the HEP related education and research training
evolution from a student to faculty level and with examples of training and
programs indicated at different levels. It is important to point out that we
must find ways to make sure that diversity, equity and inclusiveness
percolates all the way upwards from the bottom to the pyramid of Figure 1.

Figure 1: Evolution of HEP Education and Training

Some of the current training programs in the field of HEP are described below.
It would be very beneficial if some of such training could accorded course
credit, even if taken during the summer, so that not only highly competitive
students but a bigger subset of students is encouraged and able to take part.
And the scientists, faculty, and postdocs involved engaged in these training’s
should be given compensation for their significant time investment.

###  5.1 Software Training

No one size fits all while imparting software training. A possible HEP wide
solution is to exploit our large-scale community structure and organize
training within our research domains [6]. Recent successful and ongoing
efforts like IRIS-HEP [7], FIRST-HEP [8] and HEP Software Foundation (HSF) [9]
have taken strong and effective steps in this direction and impart training to
those within the field and ancillary fields. The HEP community must play a
role in bringing together a focus on these efforts to engender sustainability
and scalability. It is important to initiate learning early on in the process
of preparing a software-equipped future particle physicist.

At PUIs and CCs, and often at R1 universities, students pursuing undergraduate
degrees in physics do not necessarily get exposed to all the core
undergraduate physics and computing courses that are related with research.
When going on to go graduate school, these students may lag behind their
peers. While the curricular issue of what core physics courses are taught at
student’s institution may be challenging to address, nevertheless we can and
should develop a way for students to take elective Particle Physics courses
that give them university credit, and in addition provide HEP training in
related software. While students may exit at different levels in the HEP
education and training pyramid of Figure 1, we should try to make sure that
opportunities for training reach all.

The software training programs of IRIS-HEP and HSF have trained over 1500
undergrads, Masters, PhDs, postdocs and senior physicists with software skills
over the last 3 years, even in times of COVID-19 challenges. One of the
commendable achievements of software training has been the building of
community around LHC experiments [10] and DUNE [11]. Nuclear Physics, which
has similar educational needs, is also engaged with their effort led by
Jefferson Lab (TJNAF).

###  5.2 Training Internships

Internship programs by DOE [12] and NSF/REU [13] have been very popular to
encourage students to gain valuable research experience and are highly
competitive. For example DOE sponsored internships like SULI [14] place
undergraduate physics or engineering majors in paid summer internships. These
internships [15] offer a chance for students and professionals (school
teachers and visiting faculty) to work with scientists or engineers on
projects at the frontier of scientific research in particle physics. For all
students, but particularly those from academic departments that are primarily
PUI or masters degree oriented and which often attract community college
transfers, the opportunities afforded by extended visits to national
laboratories are truly life changing. Efforts by Wichita State University to
attract and train students for STEM careers is an excellent example of such
efforts on behalf students by dedicated and creative faculty.

###  5.3 Experiment Training Efforts

Several experiments have their own unique programs to train new collaborators
- PhDs, postdocs or faculty in all aspects of experiment. The CMS Experiment
[16, 17] and its contingent of US physicists (USCMS) that maintains the
Fermilab LHC Physics Center (LPC) [18] and an independent LHCb Experiment
program [19] are examples of very successful stories. The LPC has recently
started a Summer Undergraduate Research Internship program to train students
on HEP specific topics like detector hardware, physics analysis and software.
Through such a program, students interested in HEP can be trained early on and
the skills are translatable to other STEM areas, should the students choose to
go in other career directions.

It is notable that the R&D and construction phase of a typical HEP
experimental project can span several years and often a decade or more, and
affords a fertile opportunity to learn detector hardware related to HEP. And,
while major work happens at the laboratory or hosting site of the experiment,
substantial building and testing of detector components can be distributed
across the collaborating institutions, This can be broadly beneficial to
faculty and students across a wide range of participating colleges,
universities and laboratories.

Ongoing construction of the CMS Phase-2 Pixel sub-detector [20, 21] for the
CMS experiment at Cornell University and sub-detectors for MINOS [22], NOvA
[23] and Mu2e [24] experiments at Minnesota are some of the very good examples
that involve hundreds of students over the course of construction from
different STEM backgrounds at the host and collaborating institutions. Figure
2 shows the spectrum of undergraduates and their major fields of study, who
were involved in the building of the NOvA detector [25]. That experience
demonstrated that undergrads can be actively and effectively engaged, alert to
and fully capable of recognizing anomalies and solving problems. The Students
and postdocs appreciated being supported as valued team members in the
detector building tasks, and for the hands on experience of how to work
collaboratively and manage the work of the various teams. Graduate students
and postdocs learned about the challenges of building a detector, managing
others, and paying attention to time and budget. Moreover, this type of
experience is compelling to a general audience and newsworthy, as one reporter
captured, “I worked in a coffee shop–this is quite different. I wanted to work
in an environment where I could live and breathe science and to be around
people who’ve had similar experiences and classes.”

Figure 2: Over 700 undergraduate students from different disciplines built
NO$v$A Detector at University of Minnesota

###  5.4 Undergraduate Research at PUI’s

Initiating meaningful opportunities for research early in a student’s career
can often lead to the life and career-altering realization that a student
actually has the capacity to be a scientist. That all-important self-
identification can be the result of well coordinated programs with committed
faculty mentors, who are teamed with graduate students and postdocs. And
access to suitable facilities is also a signature of an effective program.
Features of many research invested PUI’s are the commitment of a cadre of
mentors to attract students to the excitement of the science and attendant
research opportunities, and notably, and the participation of engaged
students, the most accomplished among them as good as any University’s best.
As access to research grade facilities may be more challenging for PUIs, we
support proposals to develop PUI-centric undergraduate research
collaborations, especially in EPSCoR states [26] [27], where program
leadership and coordination of HEP related research projects evolve to
capitalize on the diversity of talent at the nation’s smaller and likely more
rural universities and colleges.

##  6 Open Science to build HEP community

The process of sharing scientific findings in journals has been the mode of
Open Science [28] for many decades [29], and Particle Physics and Astronomy
were among the first fields to embrace this approach, fostering and sharing
open source software, open access to published work and open data for
researchers and citizen scientists. The World Wide Web, Invenio, Indico,
Inspire, Zenodo and OSG (Open Science Grid) are examples of some of the
platforms and tools provided by the domain of particle physics to the
scientific community and beyond. CERN [30] provides access to open source
hardware, open publishing and open data via the CERN Open Hardware License,
the Sponsoring Consortium for Open Access Publishing in Particle Physics
(SCOAP3 [31])and the Open Data Portal for the LHC experiments. The strength of
the particle physics HEP community lies in its openness, diversity and access
to some of the best creative talent worldwide. With the advent of tools to
operate Open Science, we are poised for an even greater and more significant
role, and in a more inclusive way.

###  6.1 Benefits

Open Science empowers the ability to collaborate, question and contribute to
sustainable scientific knowledge and process, and accelerate future
discoveries. Open data from LHC [5] is employed by educators, students, and
self-learners for teaching, learning, and research. It allows research to
maximize its impact by reaching a wider audience of participation and sharing
the findings, seeking collaborations without borders, and expanding funding
and career advancement opportunities. It is also greatly enhances the quality
and opportunities for education by making it more affordable and equitable.

###  6.2 Challenges

With opportunity comes responsibility. The particle physics community has
become fully aware, and needs to make the outside world equally aware, that
there are practical limits to making all raw data public. Besides problems of
facilitating training the public at large to analyze data, significant
additional resources are needed to support personnel to maintain the data and
to serve as consultants as outsiders attempt to use the associated software
tools for analysis, which are not typically static over experimental
lifetimes, and evolve as experimentation proceeds. Existing computing
infrastructure would not be able to support many others to access all of the
available raw data.

Recommendation:

  * •

The HEP community should define, with cogent arguments, what should be the
scope of making our data and resources publicly available, and the hardware,
software and person-power costs associated with such implementation.

###  6.3 Goals

We must strengthen existing successful methodologies, many of which have been
created and developed by the U.S. HEP Community, and explore new ways of
translating HEP resources, talent and data into Open Science. We can advance
this powerful framework to create more inclusiveness by Open Software Training
and Open Physics teaching that will propel our field and the general public
into the next phase of discoveries.

##  7 Intersection of Physics and Machine Learning

Machine Learning (ML) is becoming an integral part of physics research. Many
critical HEP algorithms for triggering, reconstruction, and analysis rely on
ML and there are entire conferences and summer schools dedicated to this
crosscutting field. Moreover, the unique constraints of physics experiments
and the ability to exploit symmetries inherent in physics data have made the
field of physics-informed ML a vibrant sub-field of Computer Science (CS)
research. However, despite the relevance and importance of this research,
pursuing a career at the intersection of these fields remains tenuous and
undefined endeavor. We must work towards finding ways about how we can better
support academic and career development at the intersection of physics and ML,
and ensure that we can continue to benefit from and contribute to state-of-
the-art ML.

###  7.1 Current Environment

HEP research has long required advanced, cutting-edge computing techniques,
and physicists have historically contributed to the development of these
methods. Over the past decades, there have been great advances in the data-
processing power of ML algorithms and these methods have been quickly adopted
by physicists to address the unique timing, memory, and latency constraints of
HEP experiments [32].

Physics is also impacting ML research. The constraints of HEP experiments and
known symmetries of physical systems create a rich environment for the
development of novel ML (see for example [33]). There are even entire
conferences and workshops dedicated to this intersection including the
Microsoft Physics ML lecture series [34] and the ML and the Physical Sciences
workshop at NeurIPS [35].

However, despite the demonstrated criticality and vibrancy of this research,
from a physics perspective the path to a sustainable research career at the
intersection of physics and ML is unclear at best. In fact, many researchers
seem to regard ML research and applications as minor side projects111Due to
the lack of community statistics on this topic, the evidence presented here is
primarily anecdotal.

There are very few physics department supported courses on ML222although [36]
provides a good example of how such a course might work and interested
students are often forced to convince CS departments to allow them to attend
graduate courses (which typically do not discuss physics-informed ML).
Furthermore, at many universities the lack of collaborative interactions
between Physics and CS departments limits opportunities for physicists to
engage with cutting-edge ML research and develop partnerships with industry
researchers333NYU [37] and UW [38] Physics collaborations with the Center for
Data Science is an excellent example of cross-department collaboration.

As a physics graduate student at a US institute it is essentially impossible
to focus one’s thesis research on ML, as most departments do not acknowledge
this as ‘physics work’ (despite the fact that these algorithms are in many
cases critical to the functioning of physics experiments and data processing).
Perhaps most egregiously, although there is now some support for this work at
the post-doc or research staff level (see IRIS-HEP [7] and IAIFI [39]), early-
career researchers are often actively advised against applying for such
positions as they constitute ‘career death sentences’.

###  7.2 Proposals for Future Work

It is clear that these issues must be addressed in order to best support and
advance our field and our researchers. An important first step is to work
towards a cultural shift around the perception of what it means to ‘be a
physicist’ and what work is considered and accepted as valid as contribution
to physics. We must value technical and software contributions in the same
manner we value analysis work and foster a supportive and educational
environment for graduate students and early-career researchers interested in
ML and physics. It benefits no one to discourage individuals from pursuing
work in this vibrant and promising field.

Concretely, this necessitates developing cross-department courses,
workshops,and research collaborations. Graduate programs should approach
technical and computing skills with the same rigor they do traditional physics
courses. Departments and advisors should be encouraged to allow students and
post-docs to work across disciplines and explore opportunities for industrial
partnerships or internships. This process should also include a reevaluation
of requirements for physics graduate theses.

The research landscapes of both physics and ML are shifting, and by adjusting
to these changes we can ensure a vibrant future for data-intensive physics and
physics-informed ML.

##  8 Conclusions

This paper addresses current needs in education and training in High Energy
Physics and how the field can be proactive and innovative in transforming
current efforts, which tend to be highly selective and generally exclusionary
in nature, into a more broadly participatory and inclusive approach, to the
benefit of all students and particularly those from underrepresented
demographic groups. There are significant pools of students and faculty across
academia and notably those at Predominantly Undergraduate Institutions and
Community Colleges that can be tapped for participation, to the benefit of a
stronger and more vibrant HEP field for the future. We can develop this
untapped talent by providing creative and innovative opportunities in HEP
specific education at undergraduate and Masters levels, and by developing
rewarding research opportunities through improved training in physics,
instrumentation R&D and software and analytical techniques. Such efforts will
not only ensure that the HEP field has the professional workforce needed to
meet the scientific challenges and discoveries that lie ahead, but also the
capability to prepare students effectively for productive careers in other
STEM fields and across the needs of our broader society.

## References

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