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Phd Optimization Research Jobs in California (NOW HIRING)

Pika

Research Intern (BS/MS/PhD)

Palo Alto, CA · On-site

We are looking for passionate Research Interns at the BS, MS, or PhD level with significant ... Work directly on large-scale mid-training, post-training, and optimization efforts for Videogen ...

PIKA Inc

Research Intern (BS/MS/PhD)

Palo Alto, CA · On-site

We are looking for passionate Research Interns at the BS, MS, or PhD level with significant ... Work directly on large-scale mid-training, post-training, and optimization efforts for Videogen ...

Skild AI

Research Engineer

San Mateo, CA · On-site

Develop and implement new algorithms for training and optimizing general-purpose robot foundation ... Preferred Qualifications * BS, MS or PhD degree in Computer Science, Robotics, Engineering or a ...

Nace AI

Research Engineer

Palo Alto, CA · On-site

... optimization. Preferred : • PhD in Computer Science, Computational Linguistics, or closely related field with focus on language models and adaptive learning systems. • Proven research and ...

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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 California?

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

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

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

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

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

Phd Optimization Research jobs near you
Infographic showing various Phd Optimization Research job openings in California as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 87% Full Time, 9% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution.

Research Intern (BS/MS/PhD)

Pika

Palo Alto, CA • On-site

Full-time, Part-time, Internship

Re-posted 21 days ago

Job description

About the Role
At Pika, we are shaping the future of creative infrastructure with real-time, multimodal generation and intelligent agentic platforms. We are looking for passionate Research Interns at the BS, MS, or PhD level with significant experience working on Videogen to join our team and make an immediate impact. In this role, you will directly contribute to mid-training and post-training efforts for Videogen models and support advanced generative systems. Familiarity with multimodal large language models (MLLMs) is valued as a bonus.
This internship is ideal for students and researchers who have hands-on Videogen experience, are excited to work at the intersection of generative AI and multimedia, and are eager to make meaningful contributions alongside top AI talent. Flexible part-time and full-time internship terms are available.
What You'll Do
  • Work directly on large-scale mid-training, post-training, and optimization efforts for Videogen models.
  • Design, prototype, and refine algorithms for high-throughput video and multimedia data pipelines.
  • Collaborate with experienced researchers and engineers on advanced AI and video generation technology.
  • Apply new research techniques and production-scale workflows to deploy Videogen advancements into real-world applications.

What We're Looking For
  • BS, MS, or PhD-level backgrounds, with demonstrated Videogen experience strongly preferred.
  • Expertise in video generation models or frameworks.
  • Proficiency in Python and ML toolkits (such as PyTorch, TensorFlow, etc.).
  • Prior exposure to multimodal LLM inference, generative models, or related areas is a bonus.
  • Fast learner who can adapt to new research and technologies quickly.
  • Excellent communicator and effective team collaborator.

What We Offer
  • Flexible internship: part-time or full-time roles available
  • Unique opportunity to make an immediate impact with Videogen and generative AI research
  • Mentorship and collaboration with innovative researchers and engineers
  • Competitive compensation and a dynamic, mission-driven environment
  • Onsite work setup, with headquarters in Palo Alto, CA

About Pika
Pika empowers creators by building cutting-edge agentic and multimedia platforms. Our mission is to remove technical barriers and make real-time generative and intelligent orchestration accessible to everyone. If you are ready to accelerate your AI career, hone your video generation expertise, and contribute to the next wave of creative technology, we want to hear from you.

Apply