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Phd Optimization Research Jobs in Michigan (NOW HIRING)

micro1 AI

AI Training Specialist - Physics

Grand Rapids, MI · On-site +1

$80 - $150/hr

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... PhD in physics and an active record of independent research within a specialized subfield (e.g ...

micro1 AI

Senior Scientific Reviewer - Physics

Warren, MI · On-site +1

$80 - $150/hr

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... PhD in physics and an active record of independent research within a specialized subfield (e.g ...

micro1 AI

AI Training Specialist - Physics

Ann Arbor, MI · On-site +1

$80 - $150/hr

Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the ... PhD in physics and an active record of independent research within a specialized subfield (e.g ...

micro1 AI

AI Training Specialist - Chemistry

Warren, MI · Remote

$70 - $90/hr

... and research domain. In this role, you'll apply your expertise to help train next-generation AI ... Advanced degree (PhD preferred) in Chemistry or closely related field. * Extensive hands-on ...

micro1 AI

AI Training Specialist - Chemistry

Dearborn, MI · Remote

$70 - $90/hr

... and research domain. In this role, you'll apply your expertise to help train next-generation AI ... Advanced degree (PhD preferred) in Chemistry or closely related field. * Extensive hands-on ...

micro1 AI

AI Training Specialist - Chemistry

Detroit, MI · Remote

$70 - $90/hr

... and research domain. In this role, you'll apply your expertise to help train next-generation AI ... Advanced degree (PhD preferred) in Chemistry or closely related field. * Extensive hands-on ...

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Phd Optimization Research information

What is a PhD in optimization research?

A PhD in Optimization Research is an advanced academic degree focused on developing and analyzing mathematical models and algorithms to find the best possible solutions to complex problems. This field often involves linear and nonlinear programming, combinatorial optimization, and stochastic processes, and is applied in areas such as operations research, machine learning, logistics, and engineering. Graduates are prepared for careers in academia, industry, or research institutions, where they work on improving decision-making processes and resource allocation. The program typically involves coursework, comprehensive exams, and original research leading to a dissertation.

What are the typical collaborative projects that a PhD optimization researcher might work on within a multidisciplinary team?

PhD Optimization Researchers often collaborate on projects that integrate expertise from fields such as data science, engineering, computer science, and business analytics. These projects may involve developing and implementing advanced optimization algorithms to solve complex, real-world problems like supply chain management, resource allocation, or energy systems modeling. Team members typically contribute domain knowledge, data, and problem requirements, while the optimization researcher focuses on model formulation, algorithm selection, and solution analysis. Effective communication and adaptability are essential, as researchers must translate technical findings into actionable insights for stakeholders.

What are the key skills and qualifications needed to thrive as a PhD optimization researcher, and why are they important?

To excel as a PhD Optimization Researcher, you typically need a doctorate in applied mathematics, computer science, operations research, or a related field, along with expertise in mathematical modeling and algorithm development. Proficiency with programming languages such as Python, MATLAB, or C++, and familiarity with optimization libraries and tools like Gurobi or CPLEX are commonly required. Strong analytical thinking, creativity, and effective communication skills help in formulating novel solutions and collaborating with interdisciplinary teams. These competencies are crucial for advancing research, solving complex optimization problems, and effectively disseminating findings within both academic and industry settings.

What is the difference between Phd Optimization Research vs Data Scientist?

AspectPhd Optimization ResearchData Scientist
Required CredentialsPhD in Operations Research, Applied Mathematics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; some roles prefer PhD
Work EnvironmentResearch labs, academia, R&D departments in industryTech companies, finance, healthcare, consulting firms
Industry UsageFocus on developing optimization algorithms, mathematical modelingFocus on data analysis, machine learning, predictive modeling
Common Search/ComparisonYesYes

While both roles involve advanced analytical skills, Phd Optimization Research primarily focuses on developing and refining optimization algorithms and mathematical models, often in research or academic settings. Data Scientists analyze large datasets to extract insights and build predictive models, often applying machine learning techniques. The roles overlap in data analysis and quantitative skills but differ in their core focus and typical work environments.

What are popular job titles related to Phd Optimization Research jobs in Michigan?

For Phd Optimization Research jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Phd Optimization Research jobs in Michigan look for?

The top searched job categories for Phd Optimization Research jobs in Michigan are:

What cities in Michigan are hiring for Phd Optimization Research jobs?

Cities in Michigan with the most Phd Optimization Research job openings:

Phd Optimization Research jobs near you

Physics Content Evaluator (LaTeX/Python)

micro1 AI

Sterling Heights, MI • On-site, Remote

$80 - $150/hr

Part-time

Posted 20 days ago

Job description

Role Title: Physics Expert (Postdoc / Junior professor)


Role Type: Contractor


Location: Remote (US, Canada, UK focused)


micro1 is engaging Physics Experts (Postdoc / Junior professor) to participate in a high-impact project supporting a customer in the science and technology sector. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Critically evaluate and review physics solutions, mathematical derivations, and theoretical arguments generated by researchers or AI platforms.
  2. Detect errors, unjustified steps, missing assumptions, dimensional inconsistencies, and weaknesses in logic or methodology.
  3. Delineate between substantive scientific issues and stylistic or cosmetic matters, providing technically precise written feedback.
  4. Articulate and document the reasoning behind any identified flaws, ensuring actionable guidance for improvement.
  5. Recognize when correct reasoning can be optimized, and offer suggestions to sharpen or clarify the argument.
  6. Utilize LaTeX, SymPy, Python, and Jupyter to independently verify or counter-check scientific claims as appropriate.
  7. Deliver structured feedback designed to support iterative enhancement of submitted work and project outcomes.


Preferred Qualifications

  1. PhD in physics and an active record of independent research within a specialized subfield (e.g., High Energy/Mathematical Physics, Biophysics/Statistical Physics, Condensed Matter, AMO/Quantum Optics, Gravitation/Cosmology, Quantum Information, or Optical Materials).
  2. Experience as a postdoctoral researcher, research fellow, junior/assistant professor, or senior research scientist.
  3. Recent (last ~5 years) representative publications in the relevant subfield, with arXiv or DOI links.
  4. Advanced proficiency with LaTeX, SymPy, Python, and Jupyter for theoretical modeling and computational validation.
  5. Demonstrated skill in reviewing the work of others—through peer review, supervision, dissertation committees, or group seminars.
  6. Exceptional written communication skills with the ability to convey nuanced, constructive feedback with technical rigor.
  7. Reliable access to high-speed internet and a computer suitable for rigorous technical work.

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