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Phd Machine Learning Jobs in Rancho Cucamonga, CA

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Phd Machine Learning information

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$14

$23

$31

How much do phd machine learning jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for phd machine learning in Rancho Cucamonga, CA is $23.32, according to ZipRecruiter salary data. Most workers in this role earn between $20.14 and $26.06 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.

What cities near Rancho Cucamonga, CA are hiring for Phd Machine Learning jobs? Cities near Rancho Cucamonga, CA with the most Phd Machine Learning job openings:
Infographic showing various Phd Machine Learning job openings in Rancho Cucamonga, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $48,508 per year, or $23.3 per hour.

Staff Scientist - Computational Data Sciences Shared Resource

City of Hope

Duarte, CA

Full-time

Re-posted 21 hours ago


City Of Hope rating

8.4

Company rating: 8.4 out of 10

Based on 89 frontline employees who took The Breakroom Quiz

25th of 887 rated healthcare providers


Job description

Join the forefront of groundbreaking research at the Beckman Research Institute of City of Hope, where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine through cutting-edge research.

We are looking for a Staff Scientist for the Computational Data Sciences Shared Resource.  You will provide advanced analytical, computational, and scientific support for research programs across City of Hope, including cancer, diabetes, and broader translational sciences. Working under the leadership of the Shared Resource Director, this position delivers expert services in bioinformatics, multi‑omics data analysis, computational biology, predictive modeling, and computational oncology.

You will function as a senior technical and scientific contributor, collaborating directly with research teams to design studies, analyze data, interpret results, and support grant development. You will also contribute to implementing and maintaining analytical pipelines, training users, and ensuring that core services meet CCSG expectations for rigor, reproducibility, and impact.

Core Services:

·         Bioinformatics, multi‑omics data analysis & QC

·         Computational biology, predictive modeling, and AI/ML methods

·         Data visualization, results interpretation, and collaborative consulting

·         Training, documentation, and data science literacy support

As a successful candidate, you will be:

·         Provide high‑level analytical support across genomics, transcriptomics, proteomics, imaging, and clinical/translational datasets.

·         Implement, maintain, and document computational workflows and pipelines that ensure robust, reproducible analyses.

·         Consult with investigators on study design, computational strategies, data quality, and interpretation of results.

·         Develop and apply innovative computational methods, including machine learning and mathematical modeling approaches.

·         Prepare analysis reports, figures, methods documentation, and contributions to manuscripts and grant applications.

·         Collaborate closely with the Director to improve service intake processes, ensure timely delivery, and maintain user satisfaction.

·         Support compilation of metrics, service logs, and impact summaries for CCSG reporting and institutional reviews.

·         Contribute to workshops, training sessions, documentation, and efforts to build computational capacity among research teams.

·         Work with IT and informatics partners to support the computational infrastructure required for core operations.

·         Maintain a high standard of scientific integrity, confidentiality, and compliance with institutional data governance policies.

·         Develop staffing plans, and equipment acquisitions to ensure sustainability and innovation in core operations.

Your qualifications should include:

·         PhD or equivalent degree in bioinformatics, computational biology, mathematics, physics, engineering, computer science, or a related quantitative discipline; Or equivocal demonstrated track record through publications and prior work experience.

·         Demonstrated expertise in computational methods used in biomedical and translational research.

·         Experience working with multi‑omics datasets (e.g., genomics, transcriptomics, proteomics, single‑cell, imaging).

·         Strong programming proficiency in relevant languages (e.g., R, Python, MATLAB, Bash) and experience using HPC or cloud environments.

·         Proven ability to collaborate effectively with interdisciplinary teams, including bench scientists and clinical researchers.

·         Strong analytical, problem‑solving, and communication skills, including experience presenting scientific results.

·         Track record of contributing to peer‑reviewed publications.

·         Experience preparing analysis documentation, reports, or grant‑related materials preferred.

·         Familiarity with peer review funding mechanisms is desirable but not required.

City of Hope employees pay is based on the following criteria: work experience, qualifications, and work location.

City of Hope is an equal opportunity employer.

To learn more about our Comprehensive Benefits, please CLICK HERE.


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About City of Hope

Sourced by ZipRecruiter

City of Hope is an independent biomedical research and treatment organization for cancer, diabetes and other life-threatening diseases. Founded in 1913, City of Hope is a leader in bone marrow transplantation and immunotherapy such as CAR T cell therapy. City of Hopes translational research and personalized treatment protocols advance care throughout the world. Human synthetic insulin, monoclonal antibodies and numerous breakthrough cancer drugs are based on technology developed at the institution. AccessHope, a subsidiary launched in 2019 serves employers and their health care partners by providing access to City of Hopes specialized cancer expertise. City of Hope is ranked among the nations Best Hospitals in cancer by U.S. News & World Report and received Magnet Recognition from the American Nurses Credentialing Center. Its main campus is located near Los Angeles, with additional locations throughout Southern California and in Arizona.

Industry

Hospitals

Company size

1,001 - 5,000 Employees

Headquarters location

Duarte, CA, US

Year founded

1913