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Physics Informed Machine Learning Jobs in Illinois

Darwill, Inc.

Machine Learning Engineer

Villa Park, IL · On-site

MACHINE LEARNING ENGINEER (MLOPS / DATA ENGINEERING) Overview Darwill is a nationally recognized ... Stay informed on emerging AI technologies and tooling (GenAI is not the primary focus of this role ...

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127K - $167K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through ...

IMC Inc

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

Hardware Machine Learning Engineer Chicago, United States; New York, United States We are deploying ... Advanced degree (MS or PhD ) in EE, CS, Physics, or related field, or equivalent depth through ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Advanced degree (MS or PhD) in EE, CS, Physics, or related field, or equivalent depth through ...

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Physics Informed Machine Learning information

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 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 popular job titles related to Physics Informed Machine Learning jobs in Illinois? For Physics Informed Machine Learning jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Illinois look for? The top searched job categories for Physics Informed Machine Learning jobs in Illinois are:
What cities in Illinois are hiring for Physics Informed Machine Learning jobs? Cities in Illinois with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Illinois as of June 2026, with employment types broken down into 1% Locum Tenens, 83% Full Time, 12% Part Time, 2% Contract, and 2% Nights. Highlights an 77% Physical, 2% Hybrid, and 21% Remote job distribution.
Postdoctoral Appointee - AI for Synchrotron Imaging

Postdoctoral Appointee - AI for Synchrotron Imaging

Argonne National Laboratory

Lemont, IL • On-site

$49K - $67K/yr

Full-time

Posted 26 days ago

Job description

Job Summary:
Argonne National Laboratory is a leading research institution focused on advanced scientific discovery, and they are seeking a Postdoctoral Appointee to join their Computational Science and Artificial Intelligence Group. This role involves developing learning-enabled imaging methods for synchrotron datasets, collaborating with experts across various scientific domains to enhance understanding of microbial communities within soil.
Responsibilities:
• Develop learning-enabled algorithms for 3D reconstruction of noisy and heterogeneous synchrotron datasets.
• Implement adaptive acquisition strategies that guide beamline measurements in real time to increase efficiency and improve image quality.
• Advance multimodal analysis methods that align and fuse structural, chemical, and biological signals to construct coherent models of microbial organization across scales.
Qualifications:
Required:
• Ph.D. completed in the past 5 years or soon-to-be completed in Electrical Engineering, Computer Science, Applied Mathematics, Physics, or a related field.
• Strong expertise in machine learning, computational imaging, computer vision, or signal processing.
• Proficiency in scientific programming and modern ML frameworks, with the ability to implement and debug research-grade algorithms.
• Demonstrated ability to work on complex data analysis problems and deliver robust computational solutions.
• Excellent communication skills and a strong interest in interdisciplinary collaboration.
• Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
• Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory.
Preferred:
• Experience with synchrotron or tomographic imaging datasets.
• Background in inverse problems or physics-informed machine learning.
• Exposure to scientific imaging applications (for example, biological, environmental, or materials science).
Company:
Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management. Founded in 1946, the company is headquartered in Lemont, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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