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Machine Learning Postdoc Jobs in Houston, TX (NOW HIRING)

MD Anderson

Postdoctoral Fellow - Imaging Physics

Houston, TX · On-site

$46K - $63K/yr

A postdoctoral fellowship position is available in the Department of Imaging Physics in the ... Experience with machine learning and deep learning techniques, statistical modeling, biomechanical ...

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Machine Learning Postdoc information

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How much do machine learning postdoc jobs pay per year?

As of Jun 16, 2026, the average yearly pay for machine learning postdoc in Houston, TX is $110,487.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,214.00 and $152,166.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Postdoc position, and why are they important?

To thrive as a Machine Learning Postdoc, you need a deep understanding of machine learning algorithms, statistical modeling, and research methodology, typically supported by a completed PhD in a related field. Proficiency with programming languages like Python or R, experience with ML libraries (e.g., TensorFlow or PyTorch), and familiarity with large-scale datasets and cloud computing platforms are important. Strong analytical thinking, effective communication, and the ability to collaborate across multidisciplinary teams are standout soft skills in this position. These qualifications ensure innovative research contributions, successful project execution, and effective dissemination of findings in both academic and applied settings.

What is a Machine Learning Postdoc job?

A Machine Learning Postdoc is a research-focused position typically held after earning a Ph.D. in a related field. It involves conducting advanced research in machine learning, developing new algorithms, and publishing in top-tier conferences and journals. Postdocs often collaborate with faculty, industry partners, and other researchers to advance the state of the art in AI. The role may include mentoring students and contributing to grant proposals. It serves as a bridge between doctoral studies and a long-term academic or industry research career.

What are the typical responsibilities and collaborative aspects of a Machine Learning Postdoc position?

A Machine Learning Postdoc typically conducts original research, develops and tests new algorithms, and contributes to academic publications or patent applications. Daily tasks often involve data analysis, model building, and experimentation using advanced computational tools. Collaboration is key in this role, as postdocs frequently work alongside faculty, graduate students, and external industry partners to advance research objectives. Additionally, they may mentor junior researchers or students, present at conferences, and participate in grant writing or project planning. This mix of independent research and team collaboration fosters both professional growth and impactful scientific advancements.

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Postdoctoral Fellow - Imaging Physics

Postdoctoral Fellow - Imaging Physics

MD Anderson Cancer Center

Houston, TX • On-site

$46K - $63K/yr

Full-time

Posted 13 days ago

MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 164 frontline employees who took The Breakroom Quiz

34th of 872 rated healthcare providers

Job description

A postdoctoral fellowship position is available in the Department of Imaging Physics in the laboratory of Kristy Brock, Ph.D.
The Morfeus Lab at MD Anderson ( https://www.mdanderson.org/research/departments-labs-institutes/labs/morfeus-laboratory.html) is led by Dr. Kristy Brock. Our research is focused on the development and application of deformable image registration algorithms, artificial intelligence (AI) algorithms, biomechanical modeling, and image guided cancer therapy technologies for strategic research collaborations and clinical translation. Our lab is a highly collaborative research training environment in a state-of-the-art imaging facility and world class resources. Ongoing projects seeking postdocs include:
1) Image-guided liver surgery
2) Image-guided head and neck surgery
3) Cancer risk assessment and outcomes prediction using artificial intelligence
4) Validating in vivo imaging signals using correlative pathology
5) Image-guided focal liver ablation
6) Dose accumulation for personalized adaptive radiation therapy
LEARNING OBJECTIVES
This postdoctoral fellow will engage in computational research projects in image guided cancer therapy, including research, design, and implementation of deformable image registration, biomechanical modeling, and artificial intelligence technologies. The fellow will expand their knowledge and skills in imaging physics, data mining, predictive modeling, clustering, and classification and will develop, train, and apply deep learning in large data environments. The fellow will help to guide research and clinical collaborations and work with collaborators to integrate image guided cancer therapy models and technologies into the clinical workflow. They will collaborate and coordinate with research and clinical stakeholders and communicate findings via abstracts, poster and podium presentations, and publications.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
ELIGIBILITY REQUIREMENTS
Applicants should have earned a PhD in one of the natural sciences, computer sciences, engineering, or related fields or a medical degree. Experience with machine learning and deep learning techniques, statistical modeling, biomechanical modeling, or image registration and analysis is preferred.
POSITION INFORMATION
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
FACULTY MENTOR
Dr. Kristy Brock

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