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Phd Machine Learning Jobs in Michigan (NOW HIRING)

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Applied Scientist Intern

Ann Arbor, MI · On-site

$14.75 - $19.50/hr

... PhD program in a relevant discipline or a Master's program with research experience. * Have an understanding and experience with Natural Language Processing, and/or Machine Learning methods ...

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Showing results 41-60

Phd Machine Learning information

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$12

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$27

How much do phd machine learning jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for phd machine learning in Michigan is $19.89, according to ZipRecruiter salary data. Most workers in this role earn between $17.16 and $22.21 per hour, depending on experience, location, and employer.

What is a PhD in machine learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

What are the key skills and qualifications needed to thrive as a PhD-level machine learning professional?

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

What is the difference between Phd Machine Learning vs Data Scientist?

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

How much does a PhD in machine learning make?

A PhD in machine learning typically earns between $100,000 and $150,000 annually in industry roles, with salaries increasing for senior positions or in high-demand sectors. Academic positions may offer lower salaries but include research funding and teaching responsibilities.

What can you do with a PhD in machine learning?

A PhD in machine learning prepares individuals for advanced roles such as research scientist, machine learning engineer, data scientist, or AI specialist. These roles involve developing algorithms, analyzing large datasets, and applying AI techniques across industries like technology, healthcare, finance, and autonomous systems. Strong programming skills and knowledge of tools like Python, TensorFlow, or PyTorch are essential for these positions.
Infographic showing various Phd Machine Learning job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 22% Part Time, 2% Temporary, 2% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $41,373 per year, or $19.9 per hour.

Machine Learning Program Lead with Security Clearance

Ann Arbor, MI • On-site

Michigan Technological University
Colleges, Universities, and Professional Schools • 1 - 5K employees

Other

Re-posted 11 days ago


Michigan Technological University rating

8.3

Company rating: 8.3 out of 10

Based on 21 frontline employees who took The Breakroom Quiz


Job description

Michigan Technological University is an R1 technological research university founded in 1885 in Houghton. Our rural campus is situated just miles from Lake Superior in Michigan's scenic Upper Peninsula and is home to nearly 7,500 students from more than 60 countries around the world. Consistently ranked among the best universities in the country for return on investment, Michigan’s flagship technological university offers more than 185 undergraduate and graduate degree programs. Research focus areas include defense, health, energy, automotive, environment, and aerospace. The area’s waters, forests, and snowfall support year-round recreation, including skiing, snowboarding, hiking, biking, and paddling. The University is an integral part of the region, supported by a friendly and welcoming community that takes pride in being a true college town. We embrace our size, climate, sense of adventure, and originality. Summary At Michigan Tech Research Institute (MTRI), we develop advanced technologies that help our nation better understand, sense, and operate within complex natural and human-made environments. Our work spans multidisciplinary research and applied development, advancing ideas from foundational concepts to mission-relevant prototypes. We are seeking a senior technical leader to build, grow, and direct MTRI’s machine learning (ML) research portfolio within a government-focused R&D environment. This role will shape our ML strategy, lead business development efforts, and serve as Principal Investigator on multiple programs. This position operates at the intersection of research leadership, program execution, and institutional growth. It is not a pure software engineering role. This role is responsible for: • Leading development and execution of MTRI’s ML portfolio and growth strategy aligned with sponsor priorities • Leading capture efforts and grow a portfolio of funded ML programs • Serving as Principal Investigator on multiple programs
• Advancing ML capabilities from early-stage concepts (TRL 1–3) to prototype demonstrations (TRL 4–6) • Establishing internal ML technical standards and mentoring technical staff • Providing technical direction and mentorship across ML-related efforts. Responsibilities and Essential Duties 1. Define and maintain a multi-year ML research and growth roadmap aligned with sponsor priorities (DoD, AFRL, DARPA, etc.). 2. Identify emerging ML opportunities and shape them into competitive program concepts. 3. Develop and manage a portfolio of ML-focused research programs. 4. Contribute to institutional planning related to AI/ML capability development. 5. Lead and author technical volumes for white papers, BAAs, SBIR/STTR submissions, and other competitive proposals. 6. Demonstrate ownership of proposal strategy, technical approach, and win themes. 6. Identify and pursue new business opportunities aligned with emerging sponsor demand signals. 7. Build and maintain sponsor relationships to position MTRI for future work. 8. Develop teaming strategies and external partnerships to support transition beyond TRL 4. 9. Serve as Principal Investigator on multiple funded programs. 10. Provide overarching technical direction across ML efforts. 11. Ensure technical execution aligns with scope, budget, schedule, and performance metrics. 12. Establish rigorous experimental design, validation, and evaluation standards. 13. Oversee advancement of ML technologies from concept through prototype validation. 14. Serve as a technical authority in AI/ML within the Institute. 15. Mentor junior technical staff and guide cross-disciplinary integration across sensing, analytics, and systems teams. 16. Establish technical standards for ML reproducibility, data governance, and secure AI implementation. 17. Evaluate emerging AI hardware and software frameworks and guide adoption decisions. 18. Commit to learning about continuous improvement strategies and applying them to everyday work. Actively engage in University continuous improvement initiatives. 19. Apply safety-related knowledge, skills, and practices to everyday work. Required Education, Certifications, Licensures PhD in Computer Science, Electrical Engineering, Applied Mathematics, Physics, or closely related technical field Required Experience 1. 12–18 years of experience in applied research and development environments 2. Demonstrated experience serving as Principal Investigator on multiple funded research programs 3. Experience managing technical execution across multiple concurrent programs 4. Experience advancing technologies across TRLs, particularly from TRL 2–3 through TRL 5–6 5. Experience mentoring or supervising technical staff Desirable Education and/or Experience 1. Experience in mission-relevant domains such as remote sensing, RF sensing, geospatial analytics, or multimodal sensor fusion 2. Experience integrating ML capabilities into sensing systems or hardware platforms
3. Experience designing scalable compute architectures (cloud, hybrid, or on-prem) 4. Experience establishing MLOps or DevOps practices in research or secure environments 5. Experience implementing cybersecurity considerations for AI systems Required Knowledge, Skills, and/or Abilities 1. Ability to obtain a U.S. Department of Defense security clearance, which requires United States citizenship. Obtaining a national security clearance while holding a dual citizenship will not be possible when the foreign country poses a risk to the national security of the United States. 2. Proven track record of leading and winning competitive government research proposals 3. Demonstrated technical authority in AI/ML research or applied ML system development 4. Strong programming proficiency in Python and experience with modern AI/ML frameworks 5. Exceptional written and verbal communication skills, including experience briefing sponsors and senior leadership Desirable Knowledge, Skills, and/or Abilities 1. Familiarity with high-performance computing (HPC) or GPU-based architectures 2. Active U.S. Department of Defense security clearance at Secret-level or higher 3. Demonstrated success in, or potential future contributions to, working with persons with a wide variety of backgrounds and viewpoints Work Environment and/or Physical Demands
WORK ENVIRONMENT: The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. The noise level in the work environment is usually low to moderate. Required Training and Other Conditions of Employment Every employee at Michigan Technological University will receive the following 4 required trainings; additional training may be required by the department on a periodic basis. Required University Training:
• Employee Safety Overview
• Anti-Harassment, Discrimination, Retaliation Training
• Annual Data Security Training
• Annual Title IX Training Additional training will be required by the department on a periodic basis. Background Check:
Offers of employment are contingent upon and not considered finalized until the required background check has been performed and the results received and assessed. Please note that successful applicants must have the ability to obtain a U.S. Department of Defense security clearance, which requires United States citizenship. Obtaining a national security clearance while holding a dual citizenship will not be possible when the foreign country poses a risk to the national security of the United States.
Full-Time Equivalent (FTE) % (1=100%)
1 FLSA Status Exempt Appointment Term 12 months Shift - Pay Rate/Salary Salary is commensurate with experience and qualifications. Title of Position Supervisor Executive Director Posting Type Dependent on Funding
True Additional Information This position is contingent upon the continued availability of external funding. To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. If you require any auxiliary aids, services, or accommodations during Michigan Tech’s hiring process please notify the Human Resources office at 906-487-2280 or . Other Conditions of Employment:
Please note that successful applicants are responsible for ensuring their eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of your appointment, and maintain eligibility without sponsorship throughout your appointment. Michigan Technological University is an Equal Opportunity Educational Institution/Equal Opportunity Employer that provides equal opportunity for all, including protected veterans and individuals with disabilities.   The Annual Security and Fire Safety Report contains current campus safety and disciplinary policies, crime statistics for the previous 3 calendar years, and on-campus student housing fire safety policies and fire statistics for the previous 3 calendar years. Michigan Tech will provide a paper copy upon request; please contact the Michigan Tech Public Safety. In compliance with the federal Drug-Free Schools and Communities Act (DFSCA) and its implementing regulations (34 CFR Part 86), Michigan Tech is committed to maintaining a drugfree campus environment and actively promoting the health and safety of its community. Find our notice that outlines the University's policies, legal sanctions, health risks, and available support resources related to the unlawful possession, use, or distribution of illicit drugs and alcohol. Re

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