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Artificial Intelligence Machine Learning Physics Jobs in Utah

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

Have a graduate degree (masters or PhD) in artificial intelligence, machine learning, operations research or equivalent self study and experience * Have strong programming skills in Python and ...

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Artificial Intelligence Machine Learning Physics information

What are the key skills and qualifications needed to thrive as an artificial intelligence machine learning physicist, and why are they important?

To thrive as an Artificial Intelligence Machine Learning Physicist, you need a strong background in physics, advanced mathematics, computer science, and experience with machine learning algorithms, typically supported by a graduate degree in a related field. Proficiency in programming languages such as Python or C++, machine learning frameworks like TensorFlow or PyTorch, and familiarity with data analysis tools are essential, along with experience in scientific computing. Critical thinking, problem-solving, and strong communication skills help you interpret complex data, collaborate across disciplines, and convey research findings effectively. These combined skills are crucial for developing innovative AI models, driving scientific discovery, and advancing technology at the intersection of physics and machine learning.

What is artificial intelligence machine learning physics?

Artificial Intelligence Machine Learning Physics is an interdisciplinary field that applies AI and machine learning techniques to solve complex problems in physics. Experts in this area use algorithms to analyze large datasets, model physical phenomena, and accelerate scientific discoveries. The field combines knowledge of physics, computer science, and mathematics to design models that can predict, simulate, or interpret physical processes. Applications include materials science, quantum mechanics, astrophysics, and more, making it a rapidly growing area of research and industry.

What collaborative projects can professionals in artificial intelligence machine learning physics expect to work on?

Professionals in Artificial Intelligence Machine Learning Physics often work on interdisciplinary teams, partnering closely with data scientists, physicists, and software engineers. They may contribute to projects such as developing advanced simulation tools, optimizing experimental data analysis, or creating machine learning models to predict physical phenomena. Collaboration is key, as these roles frequently involve integrating AI algorithms with physical models and leveraging domain-specific knowledge from physics experts. This dynamic environment fosters continual learning and offers opportunities to lead innovative research or transition into specialized engineering and research leadership roles.

What is the difference between Artificial Intelligence Machine Learning Physics vs Data Scientist?

AspectArtificial Intelligence Machine Learning PhysicsData Scientist
Required credentialsDegree in Computer Science, Physics, or related fields; certifications in AI/MLDegree in Statistics, Mathematics, Computer Science; certifications in data analysis
Work environmentResearch labs, tech companies, academia focusing on AI/ML applications in physicsBusiness, finance, healthcare sectors analyzing large datasets
Industry usageDeveloping AI models for physics simulations, research, and technologyExtracting insights from data to inform business decisions

Artificial Intelligence Machine Learning Physics and Data Scientist roles share a focus on data analysis and technical skills. However, AI/ML Physics emphasizes developing algorithms within physics contexts, while Data Scientists focus on analyzing diverse datasets across industries. Both roles often require similar educational backgrounds and certifications, but their applications and work environments differ significantly.

What are popular job titles related to Artificial Intelligence Machine Learning Physics jobs in Utah? For Artificial Intelligence Machine Learning Physics jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Artificial Intelligence Machine Learning Physics jobs? Cities in Utah with the most Artificial Intelligence Machine Learning Physics job openings:

Adjunct Instructor (Artificial Intelligence & Machine Learning)

Neumont College of Computer Science

Salt Lake City, UT โ€ข On-site

Full-time

Posted 4 days ago


Job description

As a Neumont University instructor you will develop leadership and mentoring skills that will enhance your career. It can be a very rewarding experience as you see students start to understand complex subjects and gain confidence in their abilities.

Neumont is looking to fill multiple adjunct faculty positions to teach (in-person) in the following area:

  • Artificial Intelligence

Neumont University is looking for tech individuals with in-industry experience to teach the following technologies:

  • Artificial Intelligence:
  • Ability to teach AI fundamentals to complete beginners in clear, accessible terms
  • Familiarity with low-code AI tools, including Microsoft Azure ML Studio
  • AI Data Modeling:
  • Proficiency in SQL/SQLite and relational database design (entity-relationship modeling through normalization)
  • Experience with dimensional modeling / data warehousing (star schemas, OLTP vs. OLAP)
  • Understanding of how data modeling supports ML pipelines (feature stores, vector stores/embeddings, train/serve skew)
  • Ability to teach query optimization, including indexes and reading query execution plans
  • Strong working proficiency in Python, sufficient to review and debug student code live in class
  • Machine Learning Foundations:
  • Comfort teaching and evaluating algorithmic complexity (Big-O: time and space)
  • Solid grounding in core ML concepts: supervised/unsupervised/reinforcement learning, overfitting, neural network fundamentals

Reinforcement Learning:

  • Solid theoretical grounding in reinforcement learning (MDPs, Bellman equations, dynamic programming)
  • Hands-on experience with Monte Carlo methods, TD learning/SARSA, Q-learning, policy gradients, and DQNs
  • Working knowledge of NumPy and PyTorch
  • Ability to teach on-policy vs. off-policy tradeoffs and deep-RL stability concepts (replay buffers, target networks)

QUALIFICATIONS:

  • Bachelor’s or higher degree in computer science or a related field AND 4 years of CS related experience (or 8 years of CS related experience without a CS degree)
  • Teaching experience preferred, but not required
  • Ability to work within the U.S. without company sponsorship

LOCATION: In-person, on campus

TIME COMMITMENT:

  • Courses begin October 5, 2026 and are 5 to 10 weeks long, depending on the course.
  • We make classes work around full-time work schedules as we offer AM and PM classes.
  • Adjuncts may spend up to 10 hours a week outside of class doing grading and familiarizing themselves with the curriculum. This time commitment lessens once they get the hang of teaching.

ADVANTAGES TO BEING A NEUMONT FACULTY MEMBER:

  • Improve the lives of students from across the nation through the power of education.
  • Opportunity to give back through educating the next generation of tech experts.
  • Experience the "light" turn on in your student's eyes as you teach and they experience true understanding.
  • Be a part of a computer science institution that focuses on creating software engineers that can DO, not just theorize.
  • Develop your teaching/mentoring skills.

Faculty at Neumont University are responsible for educating students in accordance with the Neumont teaching methodology, which focuses on active learning and engaging students in the learning environment. Faculty members are also responsible for grading and providing valuable feedback to students in a timely manner, mentoring students in groups or individually, evaluating curriculum, adapting coursework and materials as necessary to meet student learning needs, and other activities related to effective instruction.

RESPONSIBILITIES, INCLUDING BUT NOT LIMITED TO:

  • Implement best practices in teaching and project-based learning
  • Submit all new teaching materials to Neumont vault upon completion of each course
  • Work with supervisor to identify areas for personal development and course improvement
  • Utilize feedback from mid-quarter and end-of-quarter evaluations to improve teaching
  • Identify innovative teaching methods to solve curricular problems
  • Teach material defined in the course description and syllabus
  • Maintain and meet the listed student learning goals
  • Utilize the Neumont LMS to keep an updated syllabus, course materials, and grades
  • Provide a safe learning environment for students
  • Answer and deal respectfully with student complaints and problems
  • Use effective assessments that measure student learning
  • Provide timely and accurate feedback to students’ assignments, exams, projects, etc.

FAQ

I’ve never taught before, am I qualified to teach?

We hire industry professionals and help them learn how to be good teachers. Our project-based curriculum means fewer lectures and more hands-on practice. Instructors must have at least 4 years of industry experience and a bachelor’s degree in a tech related field. An additional 4 years of outstanding experience and contributions to the field may be substituted for a formal degree.

Do I have to develop the curriculum?

You will use curriculum that has been developed and refined by previous Neumont instructors. We expect that you will share your individual perspective and experiences with the students to supplement the formal curriculum.

Does Neumont offer online courses?

No. Our classes are in-person as it makes for a better teaching/learning experience.

What is the process to get started?

All instructors will go through a formal application process which includes a short teaching demonstration. We will verify your work experience and educational credentials.

NU is an equal opportunity employer and provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Neumont’s Annual Security & Fire Safety Report is available online at https://www.neumont.edu/campus-safety under the Student Life section. This report is required by federal law to comply with the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and contains policy statements and crime statistics for the school. The policy statements address the school’s policies, procedures and programs concerning safety and security. You may also request a paper copy from the Vice President, Student Affairs.