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Phd Computer Science Jobs in California (NOW HIRING)

Qualcomm

Computer Vision Engineer

San Diego, CA · On-site

$118.40K - $139.60K/yr

OR PhD in Computer or Electrical Engineering, Computer Science, or related field and 2+ years of Software Engineering, Hardware Engineering, Systems Engineering, or related work experience.

Apex Informatics

Computer Vision Engineer V

Sunnyvale, CA · On-site

$132.90K - $156.70K/yr

... computer science or equivalent relevant experience. • 5+ years of experience designing and ... Preferred Qualification: • MS or PhD in EE/CS • Theoretical knowledge in the field of computer ...

Anduril Industries

Computer Vision Engineer

Costa Mesa, CA · On-site

$118.20K - $139.40K/yr

Preferred : • MS or PhD in Robotics, Computer Science, Mechatronics, Electrical Engineering, Mechanical Engineering, or related field. • Experience with perception systems for aerial robotics or ...

JT4, LLC

Computer Scientist - openMCT

Edwards, CA · On-site

$135K - $165K/yr

Or a PhD in an associated discipline. In addition, a Computer Scientist III must possess the following qualifications: * Experience with computer-based systems and applications * Programming skills ...

JT4 LLC

Computer Scientist - openMCT

Edwards, CA

$135K - $165K/yr

Or a PhD in an associated discipline. In addition, a Computer Scientist III must possess the following qualifications: Experience with computer-based systems and applications Programming skills in ...

Apple

AI/ML Computer Vision Algorithm Engineer

Cupertino, CA · On-site

$137.60K - $162.20K/yr

... MS/PhD in Electrical Engineering, Computer Engineering, Computer Science or related fields (e.g. Applied Mathematics, Physics or Biomedical Engineering with relevant experience)Familiarity with ...

Apple

Machine Learning/Computer Vision Engineer

Sunnyvale, CA · On-site

$130.90K - $154.30K/yr

MS or PhD in computer vision, computer graphics, machine learning, computer science, computer engineering or related fields.Comprehensive understanding of diffusion models, transformers and auto ...

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Phd Computer Science information

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$55.8K

$82K

$96.7K

How much do phd computer science jobs pay per year?

As of May 29, 2026, the average yearly pay for phd computer science in California is $82,020.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,500.00 and $92,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a PhD in Computer Science, and why are they important?

To thrive as a PhD in Computer Science, you need advanced expertise in algorithms, programming, and research methodologies, typically supported by a doctoral degree in computer science or a related field. Mastery of programming languages (such as Python, Java, or C++), data analysis tools, and familiarity with version control systems like Git are commonly required, along with experience in publishing academic research. Critical thinking, problem-solving, strong written and verbal communication, and perseverance are vital soft skills for success in research and collaboration. These skills and qualifications are essential for making significant contributions to the field, driving innovation, and effectively sharing knowledge with the academic and professional community.

What are some common challenges faced by PhD Computer Science students during their research?

PhD Computer Science students often encounter challenges such as defining a clear and impactful research problem, managing long-term projects with limited guidance, and coping with the pressure to publish in top-tier conferences or journals. Balancing coursework, teaching responsibilities, and research can also be demanding. Effective time management, networking with peers and mentors, and seeking regular feedback can help students navigate these challenges and achieve their academic goals.

What is a PhD in Computer Science?

A PhD in Computer Science is the highest academic degree in the field, focused on advanced research and the creation of new knowledge in computing. It typically involves several years of coursework followed by original research culminating in a dissertation. Graduates often pursue careers in academia, research, or advanced industry roles that require deep technical expertise and problem-solving skills.

Is IT worth doing a PhD in CS?

A PhD in Computer Science can be valuable for careers in research, academia, or specialized industry roles requiring advanced expertise. It typically involves several years of study, research, and publication, and can lead to higher-level positions but may not be necessary for most industry jobs that value practical skills and experience. Consider your career goals and whether the research focus aligns with your interests before pursuing a PhD.
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Phd Computer Science jobs near you
Infographic showing various Phd Computer Science job openings in California as of May 2026, with employment types broken down into 3% As Needed, 69% Full Time, 10% Part Time, 15% Contract, and 3% Nights. Highlights an 31% Physical, 12% Hybrid, and 57% Remote job distribution, with an average salary of $82,020 per year, or $39.4 per hour.

Lead Data Scientist (Scientific Software Engineer / Computational Scientist) - Only W2

Saransh Inc

Mountain View, CA • On-site

Contractor

Posted 9 days ago

Job description

Role: Lead Data Scientist (Scientific Software Engineer / Computational Scientist)
Location: Mountain View, CA (Hybrid – 3 days a week onsite)
Job Type: W2 Contract
 
 
Note: Only Visa Independent candidates are required (No C2C or Third-party candidates)
 
 
Experience Level: Lead
 
Main Skills:
  • Python (NumPy/SciPy/CuPy)
  • C++
  • PyTorch
  • Geostatistics
  • 3D Mathematics
  • CUDA/OpenMP
  • AI-assisted coding
 
Short Overview:
  • Scientific Software Engineer or Computational Scientist with a niche background in scientific simulation, procedural generation, or computational physics.
  • This is an implementation-heavy role requiring a developer who can translate complex mathematical logic and generative ML models into performant code to solve high-dimensional geometric problems.
 
Simulation & Generative Modeling
 Seeking a deep expertise in scientific computing, procedural generation, or computational physics to build the core algorithms for our 3D subsurface modeling engine.
 
The Role:
This is an implementation-heavy position bridging procedural physics and generative ML.
 
What We're Looking For:
Core Competencies:
  • Procedural Generation: Terrain synthesis, voxel engines, noise-driven systems
  • Scientific Computing: CFD, FEA, multi-physics solvers
  • Computational Geometry: 3D mesh processing, volumetric data structures, spatial partitioning
Key Responsibilities:
  1. Algorithmic Implementation — Design memory-efficient algorithms for massive 3D voxel arrays and sparse data structures; implement deterministic and stochastic geometric rules
    • Example: Build C++/Python kernels using 3D Perlin/Simplex noise and vector fields to simulate braided river systems
    • Example: Implement Boolean CSG algorithms for volumetric injections of igneous bodies
  2. Generative ML Engineering — Architect and train models (GANs, Diffusion) for high-resolution 3D spatial data using PyTorch
    • Example: Generate realistic fracture networks via 3D generative models
    • Example: Apply neural style transfer to map sedimentary textures onto volumetric frameworks
 
Required Technical Skills:
  • Languages: Expert Python (NumPy/SciPy/CuPy); proficient C++ for performance kernels
  • Mathematics: Linear algebra, vector calculus, coordinate transformations
  • ML Frameworks: PyTorch (generative AI, computer vision)
  • Performance: CUDA/OpenMP; parallel computing experience
  • Workflow: AI-assisted coding for rapid prototyping and testing
 
Domain Knowledge:
Mathematical maturity in:
  • Structural modeling
  • Sedimentology
  • Tectonics
  • Geostatistics
 
Ideal Background:
  • MS/PhD in Computer Science, Applied Mathematics, Computational Physics, or equivalent
  • Portfolio/GitHub demonstrating procedural world-building, physics engines, or scientific simulators