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Human Performance Phd Jobs in Santa Rosa, CA (NOW HIRING)

Human Performance Phd information

See Santa Rosa, CA salary details

$29K

$48.4K

$65.6K

How much do human performance phd jobs pay per year?

As of Jul 28, 2026, the average yearly pay for human performance phd in Santa Rosa, CA is $48,374.00, according to ZipRecruiter salary data. Most workers in this role earn between $41,000.00 and $52,500.00 per year, depending on experience, location, and employer.

What is a Human Performance PhD?

A Human Performance PhD is an advanced research degree focused on understanding and optimizing human physical capabilities, health, and well-being. Students in this program typically study topics such as exercise physiology, biomechanics, motor learning, and sports psychology. Graduates often pursue careers in academia, research, sports science, or health-related fields. The program involves both coursework and original research culminating in a dissertation. This degree prepares individuals to contribute to advancements in human performance and health.

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

To thrive as a Human Performance PhD, you need advanced knowledge in exercise science, physiology, biomechanics, and research methodology, typically supported by a doctoral degree in a related field. Experience with statistical analysis software like SPSS or R, lab equipment for physiological testing, and relevant research certifications are commonly required. Exceptional analytical thinking, communication, and collaboration skills help you design studies, publish findings, and work with multidisciplinary teams. These competencies are crucial for driving innovation, ensuring valid research outcomes, and enhancing performance strategies in academic or applied settings.

What are some common challenges faced by Human Performance PhD professionals when transitioning from academia to industry roles?

Human Performance PhD professionals often find that transitioning from academia to industry requires adapting to faster-paced project timelines, a greater emphasis on teamwork, and a need for clear, actionable results. Unlike academia, where research depth and publication are prioritized, industry roles typically focus on practical applications, data-driven decision-making, and collaboration with multidisciplinary teams. Building strong communication skills and learning to translate research findings into solutions that address business needs are key to a smooth transition.

What is the difference between Human Performance Phd vs Human Factors Specialist?

AspectHuman Performance PhdHuman Factors Specialist
Required CredentialsPhD in Human Performance or related fieldBachelor's or Master's in Human Factors or related field, often with certifications
Work EnvironmentResearch institutions, academia, or advanced consultingIndustry settings, technology companies, government agencies
Employer & Industry UsageResearch-focused organizations, universitiesDesign, usability, safety in tech, aerospace, healthcare

While both roles focus on optimizing human interaction with systems, a Human Performance Phd typically involves advanced research and academic work, whereas a Human Factors Specialist applies practical design and usability principles in industry settings. The Phd is more research-oriented, while the specialist role emphasizes applied skills in real-world environments.

What job categories do people searching Human Performance Phd jobs in Santa Rosa, CA look for? The top searched job categories for Human Performance Phd jobs in Santa Rosa, CA are:
What cities near Santa Rosa, CA are hiring for Human Performance Phd jobs? Cities near Santa Rosa, CA with the most Human Performance Phd job openings:
AIML - Machine Learning Manager, Red Teaming - Responsible AI and Safety

AIML - Machine Learning Manager, Red Teaming - Responsible AI and Safety

Apple

Bodega Bay, CA

Full-time

Posted 12 days ago


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 675 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Apple's Responsible AI and Safety team focuses on innovative technologies, methodologies, and research to enable fantastic user experiences and to push the frontier of machine learning. Our team is looking to hire a leader with a strong track record in Applied Research, who is passionate about ML and foundation models with a focus on responsibility, fairness, and safety. In this role, you will lead the research and application of ML methods for technologies that power breakthrough user experiences while upholding Apple's values, privacy, and quality standards.
Description
This role focuses on leading a team working on developing, carrying-out, interpreting, and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. This team is also responsible for producing safety evaluations that uphold Apple’s Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand what the evaluation means for the user experience.","responsibilities":"Proven technical leadership with 5+ years of team management or leadership experience
Demonstrated expertise in ML production deployment lifecycle, datasets, identifying data needs, and working on creative solutions, scaling and expanding data coverage through human and synthetic generation methods.
Provide technical direction and expertise to team-wide initiatives in safety auto-grading.
Use and implement data pipelines, and collaborate cross-functionally to execute end-to-end safety evaluations.
Work with highly-sensitive content with exposure to offensive and controversial content.
Preferred Qualifications
Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, EMNLP, etc.)
Experience working on Responsible AI and AI Safety
Strong organizational and operational skills working with large, multi-functional, and diverse teams.
Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable.
Minimum Qualifications
MS, or PhD in Computer Science, Machine Learning, Statistics, or related fields; or an equivalent qualification acquired through other avenues.
Experience working with generative models for evaluation and/or product development, and up-to-date knowledge of common challenges and failures.
Strong engineering skills and experience in writing production-quality code in Python.
Deep experience in foundation model-based AI programming (i.e.: using DSPy for optimizing foundation model prompts, for example) and a drive to innovate in this space.
Experience working with noisy, crowd-based data labels and human evaluations.
Pay & Benefits
This posting is not for a specific job opening and by submitting your resume you are expressing interest in being contacted about this type of role at Apple in the future.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976