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Part Time Machine Learning Research Scientist Jobs in Houston, TX

This is a part-time position working up to 20 hours per week and is funded by grant funds for one ... Strong scientific and numerical skills with meticulous attention to detail and accuracy * Ability ...

AP Research Tutor

Sugar Land, TX · Remote

$18 - $40/hr

Deep knowledge of research methodology, literature review construction, qualitative and ... learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring ...

AP Research Tutor

Houston, TX · Remote

$18 - $40/hr

Deep knowledge of research methodology, literature review construction, qualitative and ... learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring ...

Deep knowledge of research methodology, literature review construction, qualitative and ... learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring ...

AP Research Tutor

Pearland, TX · Remote

$18 - $40/hr

Deep knowledge of research methodology, literature review construction, qualitative and ... learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring ...

Prior experience developing or applying rubrics in scientific or educational contexts. * Experience with AI, machine learning, or annotation projects related to biology or microbiology. * Advanced ...

Prior experience developing or applying rubrics in scientific or educational contexts. * Experience with AI, machine learning, or annotation projects related to biology or microbiology. * Advanced ...

Showing results 41-60

Part Time Machine Learning Research Scientist information

See Houston, TX salary details

$48.2K

$124.3K

$166.2K

How much do part time machine learning research scientist jobs pay per year?

As of Sep 8, 2026, the average yearly pay for part time machine learning research scientist in Houston, TX is $124,258.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,700.00 and $165,200.00 per year, depending on experience, location, and employer.

What does a part time machine learning research scientist do?

A Part Time Machine Learning Research Scientist conducts research and development in the field of machine learning while working less than full-time hours. Their responsibilities typically include designing experiments, analyzing data, developing new algorithms, and collaborating with other researchers or engineers. They often work on specific projects or problems, contributing their expertise in machine learning to advance knowledge or improve products. This role allows for flexible scheduling, making it suitable for students, professionals with other commitments, or those seeking a better work-life balance.

What are the key skills and qualifications needed to thrive as a part time machine learning research scientist?

To thrive as a Part Time Machine Learning Research Scientist, you typically need strong skills in mathematics, statistics, and programming (especially Python), as well as an advanced degree in a relevant field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, experience with version control systems, and knowledge of data preprocessing tools are essential. Critical thinking, effective communication, and time management are important soft skills for succeeding in a flexible, research-driven environment. These abilities enable you to develop innovative models, collaborate efficiently, and contribute meaningful insights while balancing part-time responsibilities.

How does working part-time as a machine learning research scientist impact collaboration and project involvement?

As a part-time Machine Learning Research Scientist, you’ll typically coordinate closely with full-time team members to ensure smooth project handoffs and clear communication. While you may have a more flexible schedule, regular check-ins and collaborative meetings are essential to stay aligned with research goals and ongoing experiments. You may focus on specific research components or model development tasks that fit within your available hours, and it’s common to leverage digital tools for asynchronous collaboration. This structure allows you to contribute meaningfully while balancing other commitments, but staying proactive about updates and documentation is key to effective teamwork.

What cities near Houston, TX are hiring for Part Time Machine Learning Research Scientist jobs?

Cities near Houston, TX with the most Part Time Machine Learning Research Scientist job openings:

Infographic showing various Part Time Machine Learning Research Scientist job openings in Houston, TX as of August 2026, with employment types broken down into 20% Full Time, and 80% Part Time. Highlights an 100% In-person job distribution, with an average salary of $124,258 per year, or $59.7 per hour.

Research Intern - Systems Biology

MD Anderson

Houston, TX • On-site

Full-time, Part-time, Internship

Re-posted yesterday


MD Anderson Cancer Center rating

8.5

Company rating: 8.5 out of 10

Based on 172 frontline employees who took The Breakroom Quiz

12th of 898 rated healthcare providers


Job description

The laboratory focuses on cancer epigenomics, with particular emphasis on enzyme-tethering chromatin profiling technologies such as CUT&RUN, CUT&Tag, CUTAC and related methods for tissue-based molecular profiling. A major area of interest is the application of these approaches to formalin-fixed paraffin-embedded (FFPE) tissues and other clinically relevant biospecimens, with integration of pathology-guided tissue assessment and downstream molecular analysis.
This Research Intern position is a short-term, primarily wet-lab training appointment designed to provide practical experience in cancer research through direct participation in epigenomic profiling experiments. The intern will work closely with the PI, laboratory manager and research team to support established FFPE tissue profiling workflows across a large volume of specimens. This position is especially well-suited for candidates with prior hands-on research experience in molecular biology, epigenomics, or chromatin assays. Prior exposure to CUT&RUN, CUT&Tag, CUTAC, or related enzyme-tethering profiling methods is strongly preferred. Experience or interest in pathology, tissue handling, histology, or molecular profiling of clinical specimens is an advantage.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
The Research Intern will gain firsthand practical experience in epigenomic profiling for cancer research, particularly in the context of FFPE and other tissue specimens. Under close supervision, the intern will learn how established enzyme-tethering profiling workflows are implemented in a research laboratory, including sample handling, tissue-based experimental preparation, antibody-guided chromatin profiling steps, experimental quality control, and rigorous protocol documentation.
A central learning objective is to develop an applied understanding of how pathology information and tissue morphology inform molecular profiling strategy. The intern will gain exposure to how specimen quality, tissue context, and pathology-guided assessment influence experimental prioritization, assay feasibility, and interpretation of epigenomic data. This training is intended to strengthen the intern's ability to connect histologic features with molecular profiling workflows in translational cancer research.
The intern will also develop practical skills in reproducible laboratory workflow execution, including sample organization, batch processing, recordkeeping, and close coordination with the laboratory manager to support high-throughput tissue profiling activities. In addition, the intern will have the opportunity to learn how experimental data are processed and interpreted downstream, and to interact with computational members of the group to better understand the relationship between laboratory execution, data quality, and biological insight.
Expected learning outcomes include increased proficiency in tissue-based epigenomic laboratory methods, stronger understanding of pathology-informed molecular profiling, improved laboratory organization and reproducibility skills, and broader exposure to cancer research career paths at the interface of experimental and computational biology.
ELIGIBILITY REQUIREMENTS
Applicants must hold a bachelor's or master's degree in a relevant field, and the degree must have been obtained within one year of the appointment start date. Applicants must also have previous research experience in a laboratory setting relevant to biomedical, molecular, or cancer research.
Because this is a short-term wet-lab position in terms of epigenomic profiling projects, only candidates with prior hands-on experience in molecular biology, chromatin biology, epigenetics, genomics, or related experimental research, especially those with direct exposure to CUT&RUN, CUT&Tag, CUTAC, or related enzyme-tethering chromatin profiling assays, are considered. Experience with FFPE tissue, histology, pathology-associated workflows, tissue processing, or nucleic acid library preparation is desirable.
Candidates should be detail-oriented, able to follow established protocols precisely, and prepared to work collaboratively in a structured wet-lab research environment.
ADDITIONAL APPLICATION INFORMATION
Email the following to Dr. Ye Zheng at yzheng8@mdanderson.org.
• a cover letter describing detailed past experience with the enzymetethering epigenomic profiling experiments, such as CUT&RUN, CUT&Tag, and CUTAC.
• a curriculum vitae
• emails and phone numbers of a list of three references that can best describe your experimental and research skills
POSITION INFORMATION
This position (full-time or part-time) provides a stipend between $28,000 - $37,440.
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html

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