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Physics Informed Machine Learning Jobs in Georgia

Required : • A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. • At least 2+ years of industry ...

... physics, statistics, or related field. • Strong experience with applying expertise in model design, training, validation, and monitoring. • Excellent understanding of machine learning ...

... informed decision-making across the organization. This role requires strong expertise in advanced analytics, machine learning, statistical modeling, and data engineering principles. The ideal ...

Signal Processing Engineer

Atlanta, GA · On-site

$95K - $160K/yr

A Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, Mathematics, or a ... Expertise in electromagnetics, modeling & simulation, machine learning/artificial intelligence ...

Develop electronic warfare and radar system concepts, signal processing and machine learning ... PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical ...

A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. * At least 2+ years of industry experience outside ...

A Bachelor's in a quantitative field (engineering, mathematics, physics, machine learning, statistics or computer science) are the ideal candidates. * At least 2+ years of industry experience outside ...

If you are a tech-savvy leader passionate about designing and developing powerful Machine Learning ... Physics is essential. What could set you apart (nice to have skills): * Strong problem-solving ...

Develop electronic warfare and radar system concepts, signal processing and machine learning ... PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical ...

Develop electronic warfare and radar system concepts, signal processing and machine learning ... PhD, MS, or BS in Electrical Engineering, Applied Mathematics, Physics, or related technical ...

Drives the conception, prototyping, and deployment of machine learning models-particularly in ... Bachelor's degree in Computer Science, Math, Physics, Engineering, or related quantitative field ...

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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.
What are popular job titles related to Physics Informed Machine Learning jobs in Georgia? For Physics Informed Machine Learning jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Georgia look for? The top searched job categories for Physics Informed Machine Learning jobs in Georgia are:
What cities in Georgia are hiring for Physics Informed Machine Learning jobs? Cities in Georgia with the most Physics Informed Machine Learning job openings:

Data Scientist - multiple levels - CLEARANCE and POLYGRAPH REQUIRED

Constellation Technologies, Inc

Augusta, GA

$120K - $220K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago


Job description

Big Data, dataflows, Artificial Intelligence / Machine Learning (AI/ML) familiarity, Analytics in GME, Jupyter notebooks, and Spark.
 
Due to federal contract requirements, United States citizenship and an active TS/SCI security clearance and polygraph are required for the position.
 
 
Required:
  • Must be a US Citizen
  • Must have TS/SCI clearance w/ active polygraph
  • This position is open to multiple levels of years of experience; two (02) years within the last five (05) years must be directly related to the job you are applying for:
  • Level 04 requires a minimum seventeen (17) years of experience w/ Degree
  • Level 03 requires a minimum twelve (12) years of experience w/ Degree
  • Level 02 requires a minimum five (05) years of experience w/ Degree
  • Degree in Mathematics, Applied Mathematics, Statistics, Applied Statistics, Machine Learning, Data Science, Operations Research, or Computer Science. A degree in a related field (e.g., Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g., physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e., behavioral, social, and life) may be considered if it includes a concentration of coursework (typically 5 or more courses) in advanced mathematics (typically 300 level or higher; such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math courses intended to meet a basic college level requirement, or upper-level math courses designated as elementary or basic do not count.
  • Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python) and skill in at least one mid-level language (e.g. C)), data mining, advanced statistical analysis (e.g. statistical foundations of machine learning, statistical approaches to missing data, time series), advanced mathematical foundations (e.g. numerical methods, graph theory), artificial intelligence, workflow and reproducibility, data management and curation, data modeling and assessment (e.g. model selection, evaluation, and sensitivity.
  • Employ some combination (2 or more) of the following areas: Foundations (Mathematical, Computational, Statistical); Data Processing (Data management and curation, data description and visualization, workflow, and reproducibility); Modeling, Inference, and Prediction (Data modeling and assessment, domain-specific considerations).
  • Devise strategies for extracting meaning and value from large datasets.
  • Make and communicate principled conclusions from data using elements of mathematics, statistics, computer science, and application specific knowledge.
  • Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent to Agency data holdings.
  • Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.
  • Effectively communicate complex technical information to non-technical audiences.
  • Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting Agency collection, processing, storage and analytic capabilities and limitations.
These Qualifications Would be Nice to Have:
  • Fully Cleared polygraph is preferred
  • Knowledge of working with Big Data, dataflows, Machine Learning/Artificial Intelligence familiarity.
  • Analytics in GME, Jupyter notebooks, and Spark.
$120,000 - $220,000 a year
The pay range for this job, with multi-levels, is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
The benefits package:
 
Affordable healthcare options with 80% employer paid premium PLUS a company-funded HSA
Dental insurance with 100% employer paid premium
Vision with 80% employer paid premium
Employer paid Life insurance 100%
Employer paid Short-term and Long-term disability 100%
Annual training, continued education, and professional memberships reimbursement
Unlimited access to Red Hat Enterprise Linux, AWS, and NetApp training and accreditation
Annual reimbursement for technology i.e. phones, computers, printers, etc...
401(k) with company match up to 5% with 100% immediate vesting (after 90 days of employment)
 
The environment and perks:
 
Professional development investment and paid time off for training
Contract and work locations in Maryland, Virginia, Colorado, Texas, Utah, California, Florida and Hawaii.
Team building events throughout the year such as Destination Family Events, Holiday Party, Monthly Get-Togethers
Leadership Team engagement and mentorship
Performance Recognition Program
Complimentary branded apparel
 
Don't see a job opening that's the perfect fit? Apply to our General Position to join our talent pool for consideration for future opportunities.
 
Know someone else who may be a good fit? Refer them through the CTI External Referral Program and you could receive a one-time referral bonus of up to $10,000! Email [email protected] for more information.
 
Constellation Technologies is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, religion, creed, color, national origin, ancestry, sex (including pregnancy, childbirth, breastfeeding, or medical conditions related to pregnancy, childbirth, or breastfeeding), age, medical condition, marital or domestic partner status, sexual orientation, gender, gender identity, gender expression and transgender status, mental disability or physical disability, genetic information, military or veteran status, citizenship, low-income status or any other status or characteristic protected by applicable law. Job applicants can submit questions about CTI's equal employment opportunity policy to [email protected].
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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