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Physics Informed Machine Learning Jobs in Marrero, LA

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How much do physics informed machine learning jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for physics informed machine learning in Marrero, LA is $18.34, according to ZipRecruiter salary data. Most workers in this role earn between $11.44 and $23.27 per hour, depending on experience, location, and employer.

What is a physics informed machine learning?

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 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 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 popular job titles related to Physics Informed Machine Learning jobs in Marrero, LA?

For Physics Informed Machine Learning jobs in Marrero, LA, the most frequently searched job titles are:

What cities near Marrero, LA are hiring for Physics Informed Machine Learning jobs?

Cities near Marrero, LA with the most Physics Informed Machine Learning job openings:

Physics Informed Machine Learning jobs near you

Student Enrollment Advisor

NOLA Public Schools

New Orleans, LA

$30K - $47K/yr

Full-time

Re-posted 11 days ago

Job description

NOLA Public Schools Vision
The vision of the NOLA Public Schools is that every student receives a high-quality education that fosters their individual capabilities, while ensuring that they thrive, achieve physical and mental wellness, and are prepared for civic, social, and economic success. 

Position Summary 

The Student Enrollment Advisor will be responsible for serving students and families who enroll at any New Orleans public and non-public schools participating in the unified enrollment system. The Student Enrollment Advisor will primarily be responsible for early childhood eligibility verification, waitlist management, virtual assistance to families in need of enrollment services (i.e. phone, text, email, virtual appointments) and providing back-of-house support to Student Enrollment Coordinators and Family Resource Centers.  

Essential Duties and Responsibilities 

  • Provides students and families with objective, informed information regarding citywide school choice, performing back-of-house support of the application process;   

  • Provides exemplary customer service, answering incoming calls and timely response of emails;  

  • Conducts virtual appointments for families seeking enrollment assistance;  

  • Maintains conscientious student data using SalesForce, a student information platform, in alignment with district standards and State and local student privacy laws;   

  • Internalizes and implements all district guidelines pertaining to enrollment procedures and parent rights and responsibilities, including State and local guidance on specific student populations, such as students with special needs, limited English proficiency, and early childhood education students;  

  • Determines applicant eligibility for publicly funded early childhood seats by learning and understanding eligibility criteria and verifying income, residency, and other legal documents against those criteria;   

  • Document every Early Childhood account/application to reflect current family SNAP, verification, and in-person and virtual communication statuses;  

  • Successfully verify < 95% of assigned Early Childhood applications and application documents based on team expectations and EC local, state, and federal verification categories; 

  • Escalates parent and student concerns as needed to the Executive Director of Family Services, in coordination with district accountability offices and standards;   

  • Performs additional student services as needed including attendance at community events;  

  • Requires participation in occasional evenings and/or weekend enrollment events providing support for enrollment activities for New Orleans families and students throughout the year;  

  • Attends staff and other district meetings as necessary;   

  • Provides administrative support to the Executive Director of Family Services and assists Student Enrollment Coordinators as needed;  

  • Performs other duties as required.  

Educational Background 

  • High School Diploma required;  

  • 2 years of customer service experience required.  

Salary Offers
Our salary offers reflect a commitment to equity and transparency. Each offer is determined by education, years of experience, and alignment with compensation across similar roles within the district.
 
Work Environment
Listed below are key points regarding environmental demands and the work environment of the job.  Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions of the job.   
- Required to use motor coordination with finger dexterity (such as keyboarding, machine operation, etc.) part of the workday; 
- Required to exert physical effort in handling objects more than 30 pounds rarely; 
- Required to be exposed to physical occupational risks (such as cuts, burns, exposure to toxic chemicals) rarely; 
- Required to be exposed to physical environment which involves dirt, odors, noise, weather extremes or similar elements rarely; 
- Normal setting for this job is an office/school setting.     
 
Performance Evaluation
The employee will be evaluated based on the above position using either two methods: via COMPASS/LEADS or a NOLA-PS evaluating instrument. If the employee holds an Educational Leadership certification, he/she will be evaluated via COMPASS/LEADS to ensure renewal of certification.
 
EEOC Statement
NOLA Public Schools is committed to equal employment opportunities regardless of race, color, genetic information, creed, religion, sex, sexual orientation, gender identity, lawful alien status, national origin, age, marital status, and non-job related physical or mental disability, or protected veteran status.
 

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. 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.