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Physics Informed Machine Learning Jobs in Minnesota

... informed decisions. This role is hybrid, which means you will work some days at our corporate ... Utilizing cutting edge statistical and machine learning methods to dig deep into complex data to ...

Senior AI Scientist

Richfield, MN · On-site +1

$94.70K - $129.40K/yr

Bachelor's degree in a highly quantitative field (Computer Science, Engineering, Physics, Math, Operations Research or related) or equivalent experience * Strong machine learning and algorithmic ...

Senior AI Scientist

Minneapolis, MN · On-site +1

$95.50K - $130.50K/yr

Bachelor's degree in a highly quantitative field (Computer Science, Engineering, Physics, Math, Operations Research or related) or equivalent experience * Strong machine learning and algorithmic ...

Senior AI Scientist

Richfield, MN · On-site

$104.14K - $186.56K/yr

Bachelor's degree in a highly quantitative field (Computer Science, Engineering, Physics, Math, Operations Research or related) or equivalent experience * Strong machine learning and algorithmic ...

Candidates should have an established background in X-ray physics and imaging science. Skills in the development of machine learning algorithms for medical imaging tasks are desirable. Proficiency in ...

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 ...

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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 Minnesota? For Physics Informed Machine Learning jobs in Minnesota, the most frequently searched job titles are:
What cities in Minnesota are hiring for Physics Informed Machine Learning jobs? Cities in Minnesota with the most Physics Informed Machine Learning job openings:
Faculty Positions

$125K - $160K/yr

Full-time

Medical, Dental, Life, Retirement

Posted yesterday


Job description

About the Job
 

About the Job 

The Department of Electrical and Computer Engineering, University of Minnesota Twin Cities invites applications in the areas of: i) computer engineering, ii) AI, iii) Optics and photonics. These are tenure-track / tenured faculty positions, hiring at the Assistant, Associate, or Full Professor levels; rank and salary will be commensurate with qualifications and experience. 

Computer Engineering:

Expertise in chip design and verification, design automation, computer architecture, and emerging computing platforms is of particular interest, including the fields of AI/ML, heterogeneous integration, quantum, and physics-inspired computing.

Collaboration in research and development in chip design, verification methods, electronic design automation, and computer architecture. Particular application areas of interest include (but are not limited to): AI/ML accelerator design, application of AI/ML for chip design and verification, domain-specific computing, heterogeneous architectures, hardware-algorithm co-design, quantum, and physics-inspired computing.

AI: 

Expertise in algorithms, theory, and applications across the fields of artificial intelligence and machine learning are of particular interest. 

Collaboration in research and development in basic and applied research in artificial intelligence and machine learning. Theoretical areas of interest include (but are not limited to) optimization, neural networks, and reinforcement learning. Application areas of interest include (but are not limited to) robotics, foundation models, image / signal processing, optimization, and control. 

Optics and Photonics:

Expertise in the fields of optics, photonics, nanophotonics, quantum optics, optical materials, devices, instrumentation, and systems including (but not limited to): Integrated and nano-scale photonics; metasurfaces, and plasmonics; Optical manufacturing, patterning, and machining techniques; Biophotonics and optical biosensing; Optical imaging and spectroscopy; Optical measurement and sensing science and instrumentation; Quantum optics; Optoelectronics and silicon photonics; Optical communications and interconnects. 

Collaboration in research and development of one or more of the above listed fields of expertise. Candidates whose work bridges optics and photonics with emerging areas such as quantum technologies or computing, packaging, neuroengineering, biomedical diagnostics, high power devices or systems, or AI-enabled systems are particularly encouraged to apply. Demonstrated ability in micro- and/or nano-fabrication is desirable; candidates are expected to make extensive use of the Minnesota Nano Center (MNC) cleanroom facilities.

Research

  • Develop research proposals for external funding opportunities and collaborate with researchers from academia and industry on joint research projects.
  • Engage in research, publication, and scientific creation.

Teaching

  • Develop and teach undergraduate and graduate courses in the Department of Electrical and Computer Engineering.
  • Advise students regarding specific coursework and broader academic or career goals.

Service

  • Provide service through participation in governance of the department and/or the University.
  • Contribute to outreach activities that support the Department of Electrical and Computer Engineering mission.
  • Contribute to the development of the profession, keep current with the field, and broaden knowledge and expertise.
Qualifications
 

Successful candidates will have outstanding academic and research records and are expected to establish a vigorous, funded research program, teach at the undergraduate and graduate levels, and be involved in service to the University and the profession. An earned doctorate or equivalent foreign degree in an appropriate discipline is required at the time of appointment. It is anticipated that the appointment will begin Fall 2026. Completion of PhD required. 

About the Department
 

The Department of Electrical and Computer Engineering is one of the largest departments within the College of Science and Engineering at the University of Minnesota. Current research areas include Biomedical and Biological Computation Methods; Devices and Systems; Communications, Signal Processing, and Networking; Computer Engineering, VLSI, and Circuits; Fields, Photonics, and Magnetics; Micro and Nano Structures; Sustainable Energy Systems, Power Electronics and Drives; Systems and Controls. To learn more about the Department of Electrical and Computer Engineering at the University of Minnesota, please visit the department website.

Pay and Benefits
 

Pay Range: Assistant Professor $110,000-$130,000, Associate Professor $125,000-$160,000, Full Professor $135,000-$230,000; depending on education/qualifications/experience 

Time Appointment: 100% Appointment

Position Type: Faculty and P&A Staff 

Please visit the Office of Human Resources website for more information regarding benefit eligibility.

The University offers a comprehensive benefits package that includes:

  • Competitive wages, paid holidays, and generous time off
  • Continuous learning opportunities through professional training and degree-seeking programs supported by the Regents Tuition Benefit Program
  • Low-cost medical, dental, and pharmacy plans
  • Healthcare and dependent care flexible spending accounts
  • University HSA contributions
  • Disability and employer-paid life insurance
  • Employee wellbeing program
  • Excellent retirement plans with employer contribution
  • Public Service Loan Forgiveness (PSLF) opportunity
  • Financial counseling services 
  • Employee Assistance Program with eight sessions of counseling at no cost
  • Employee Transit Pass with free or reduced rates in the Twin Cities metro area
How To Apply
 

Applications must be submitted online. To be considered for this position, go to the Interfolio job site (https://apply.interfolio.com/176726) and follow the application instructions. To request an accommodation during the application process, please e-mail employ@umn.edu or call (612) 624-UOHR (8647).

Diversity
 

The University recognizes and values the importance of diversity and inclusion in enriching the employment experience of its employees and in supporting the academic mission.  The University is committed to attracting and retaining employees with varying identities and backgrounds.

The University of Minnesota provides equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression.  To learn more about diversity at the U:  http://diversity.umn.edu

Employment Requirements
 

Any offer of employment is contingent upon the successful completion of a background check. Our presumption is that prospective employees are eligible to work here. Criminal convictions do not automatically disqualify finalists from employment.

About University of Minnesota
 

The University of Minnesota, Twin Cities (UMTC)

The University of Minnesota, Twin Cities (UMTC), is among the largest public research universities in the country, offering undergraduate, graduate, and professional students a multitude of opportunities for study and research. Located at the heart of one of the nation's most vibrant, diverse metropolitan communities, students on the campuses in Minneapolis and St. Paul benefit from extensive partnerships with world-renowned health centers, international corporations, government agencies, and arts, nonprofit, and public service organizations.

At the University of Minnesota, we are proud to be recognized by the Star Tribune as a Top Workplace for 2021, as well as by Forbes as Best Employers for Women and one of Americas Best Employers (2015, 2018, 2019, 2023), Best Employer for Diversity (2019, 2020), Best Employer for New Grads (2018, 2019), and Best Employer by State (2019, 2022).