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Physics Informed Machine Learning Jobs in Kentucky

Pwc

CTIO AI Engineering Manager

Louisville, KY · On-site

$73.50K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Pwc

NGA AI Engineer Manager

Louisville, KY · On-site

$73.50K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Pwc

US Tech - AI Engineering Manager

Louisville, KY · On-site

$73.50K - $244K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Pwc

NGA AI Engineer Senior Manager

Louisville, KY · On-site

$91K - $321.50K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in data science and machine learning engineering at ...

Hart County Schools

26-27 Teacher -Science

Munfordville, KY

$37.10K - $47.90K/yr

... physics; develops students skills and abilities in scientific methods and problem-solving, as well ... student learning. - Develops lesson plans and instructional materials for subject area, and ...

Deloitte

Software Product Architect

Louisville, KY

... machine learning models for the product in the right way at the right time. Incremental and ... Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability ...

Pwc

GenAI Python Systems Engineer-Manager

Louisville, KY

$99K - $232K/yr

They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in artificial intelligence and machine learning at PwC ...

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Physics Informed Machine Learning information

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.
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Physics Informed Machine Learning jobs near you
WS - Summer - ACA Undergraduate Research Assistant - High Energy Physics - IWS

WS - Summer - ACA Undergraduate Research Assistant - High Energy Physics - IWS

University of Pikeville

Pikeville, KY • On-site

$2.80K/wk

Other

Posted 8 days ago

Job description

WS - Summer - ACA Undergraduate Research Assistant - High Energy Physics - IWS

Division: CAS Department: PHysics

Experience: Experienced

Job Code: IWSACAPHYUGRA GL Code: Exp Learning & ACA

Supervisor of Student Employee(s): Samuel Lane

FWS, IWS, or Grant Funded: FWS, IWS, Grant Funded

Avg. Hours/Week: 1-5, 6-10, 11-15, 16-20

Requested Start Date: 06/01/26 Term of Position: Summer, Fall, Spring

We seek a motivated undergraduate student to participate in a summer research project in high energy physics. The student will work closely with a faculty mentor over the course of the summer term, gaining hands-on experience in computational physics, data analysis, and machine learning applications in particle physics.

Responsibilities and Career Competencies:

Participate in regular research meetings to track progress and discuss results. (C, TW, P, CSD)

Generate and analyze simulated data using standard computational tools. (CT, T, CSD)

Learn to run and interpret simulation software using pre-developed input files and benchmark models. (CSD, CT, T)

Implement and test approaches to assess potential improvements in particle identification. (CT, T, CSD)

Analyze and compare signal and background data from Large Hadron Collider (LHC) simulations to assess detection sensitivity. (CT, T)

Contribute to the interpretation of results and preparation of research findings. (C, TW, CT, P)Competencies/Skills: Communication (C), Teamwork (TW), Professionalism (P), Career & Self Development (CSD), Critical Thinking (CT), Community Transformation (CTR), Leadership (L), Technology (T)

Qualifications: Add qualifications needed to be successful in this position.

  • Undergraduate student in physics, engineering, computer science, or a related field.
  • Interest in particle physics, computational methods, or data science.
  • Basic familiarity with programming (e.g., Python, C++, or similar) is preferred.
  • Strong motivation and willingness to learn new technical skills.

Computer Skills: Word, Excel, PowerPoint, Canva, Social Media & New Technology, Other: ___Basic Programming___________

Other Skills: Attention to detail, Strong active listening abilities, Public speaking, Written & verbal communication, Customer focused, Willingness to learn new things

Work Schedule: Su ___ to ___; M ___ to ___; T ___ to ___; W ___ to ___; R ___ to ___; F ___ to ___; Sa ___ to ___; Hours vary depending on workload (Check days that apply, insert hours if set, otherwise, check "Hours vary depending on workload".)

Work Conditions: Heat, Cold, Odors/Smoke, Toxic Agents, Dust, Machinery, Light Intensity, Noise, Vibrations, Wetness, Humidity, Electrical Currents, Other: _________________________

Physical Demands: Keyboarding, Reaching/Handling, Stooping/Kneeling, Crouching/Crawling, Pushing up to ___ lbs., Pulling up to ___ lbs., Lifting up to ___ lbs., Carrying up to ___ lbs., Climbing, Balancing, Other: _________________________

Number of Positions: 2

Pay Rate: Stipend $2,795.50, divided into 2 payments (not equal)

Location: Building: _ARM____, Room #: __204___

Application Notes: Resumes and applications will be reviewed to determine if you meet the required qualifications for the position. If it is determined that you meet the required qualifications, your application materials will be used to identify a top group of the most highly qualified candidates. The University of Pikeville is an equal opportunity employer committed to assembling a diverse, broadly trained faculty and staff. The University of Pikeville does not discriminate on the basis of race, ethnicity, color, sex, gender, gender identity, sexual orientation, religion, national origin, age or disabilities in its programs, activities, hiring, or the admission of students.

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