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Temporary Machine Learning Postdoc Jobs in Texas

Postdoc Fellow - Imaging Physics

Houston, TX

$46.80K - $63.50K/yr

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

Postdoc Fellow - Imaging Physics

Houston, TX

$46.80K - $63.50K/yr

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

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Temporary Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Temporary Machine Learning Postdoc, and why are they important?

To thrive as a Temporary Machine Learning Postdoc, you need a PhD in a relevant field, a solid grasp of machine learning theory, and strong programming skills (often in Python or R). Experience with tools such as TensorFlow, PyTorch, and high-performance computing environments, as well as a record of peer-reviewed research, is typically required. Strong analytical thinking, collaboration, and effective communication help you stand out in this research-intensive role. These skills are essential for advancing cutting-edge research, publishing impactful findings, and contributing to interdisciplinary projects.

What types of projects and collaborations can a Temporary Machine Learning Postdoc expect to engage in during their appointment?

A Temporary Machine Learning Postdoc typically works on cutting-edge research projects, often contributing to ongoing studies or initiating novel investigations within the field. Collaboration is common, both within their immediate research group and with interdisciplinary teams, such as data scientists, domain experts, or industry partners. Postdocs may also mentor graduate students, present findings at conferences, and publish papers, gaining valuable experience that can lead to academic or industry roles. The environment is fast-paced and research-driven, offering opportunities for professional growth and expanding one's research portfolio.

What is a Temporary Machine Learning Postdoc?

A Temporary Machine Learning Postdoc is a fixed-term research position, typically held at a university or research institution, focused on advancing knowledge and techniques in machine learning. Postdoctoral researchers in this role work on specific projects, often collaborating with faculty, graduate students, or industry partners. The position is designed to provide advanced training and research experience after earning a PhD, usually lasting from several months to a couple of years. Temporary postdocs may contribute to publishing academic papers, developing algorithms, and mentoring students, while preparing for longer-term academic or industry careers.

What is the difference between Temporary Machine Learning Postdoc vs Data Scientist?

AspectTemporary Machine Learning PostdocData Scientist
CredentialsPhD in Computer Science, Data Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often requires experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageUniversities, research centersBusiness, technology, finance, healthcare
Search & Comparison IntentUnderstanding research-focused roles, academic opportunitiesIndustry roles, applied data analysis, business impact

The Temporary Machine Learning Postdoc is primarily research-oriented, often in academic or research settings, requiring a PhD. In contrast, a Data Scientist typically works in industry, applying data analysis and machine learning to solve business problems, often with a Bachelor's or Master's degree. Both roles involve machine learning skills but differ in environment, focus, and experience level.

What are the most commonly searched types of Machine Learning Postdoc jobs in Texas? The most popular types of Machine Learning Postdoc jobs in Texas are:
What cities in Texas are hiring for Temporary Machine Learning Postdoc jobs? Cities in Texas with the most Temporary Machine Learning Postdoc job openings:
Postdoctoral Fellow - Biostatistics

Postdoctoral Fellow - Biostatistics

MD Anderson

Houston, TX

$64K - $76K/yr

Other

Medical, Dental, Retirement, PTO

Posted 24 days ago


MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 163 frontline employees who took The Breakroom Quiz

31st of 864 rated healthcare providers


Job description

The Department of Biostatistics at The University of Texas MD Anderson Cancer Center invites applications for a postdoctoral fellowship in Biostatistics. This position is intended for candidates interested in developing methodological research in data science and artificial intelligence, with applications to biostatistics and cancer research. The postdoctoral fellow will develop novel statistical and computational methods for the integrative analysis of multi-source biomedical data and will create software tools to support reproducible research.

The fellow will also contribute to collaborative translational studies with clinical and biological investigators, including the analysis of omics, survival, clinical trial, and other clinical data generated through cancer research at UT MD Anderson. The fellow will be jointly supervised by Dr. Xuelin Huang and Dr.

Ziyi Li and will have the opportunity to contribute to high-impact interdisciplinary projects at the interface of statistical methodology, artificial intelligence, cancer biology, and clinical research. All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations. LEARNING OBJECTIVES The postdoctoral trainee will develop advanced expertise in statistical and computational methods for clinical and survival data analysis, including high-dimensional modeling, feature extraction, multimodal data integration, and spatially informed machine learning.

The training will emphasize the development of novel biostatistical and computational methodologies, including model derivation, algorithm design, software implementation, and reproducible research practices. The trainee will further strengthen programming and computational skills for large-scale biomedical data analysis, with extensive experience in R, Python, C++, and related computational platforms. In addition, the trainee will gain hands-on experience analyzing clinical, survival, and omics data from clinical trials and translational studies, working closely with physicians and biologists to interpret findings and generate clinically meaningful insights.

Through this training, the fellow will be well prepared to design, evaluate, and apply innovative statistical and machine learning approaches to complex biomedical problems, while building a strong foundation for independent methodological research, interdisciplinary collaboration, and high-impact scientific publication in biostatistics, bioinformatics, and precision medicine. ELIGIBILITY REQUIREMENTS Applicants must have a recent PhD in biostatistics/computational science from a reputed University/Institute or within 0-1 years of graduation. At least one first author publication in a peer reviewed journal stemming from PhD studies is required.

A solid background in spatial omics, single cell data analysis, and computation is required. Some experience with machine learning and AI is desirable. ADDITIONAL APPLICATION INFORMATION Please send CV and information on three referees directly to zli16@mdanderson.org

POSITION INFORMATION MD Anderson offers full-time postdoc positions with a salary ranging from $64,000 to $76,000. depending on the number of years of postgraduate experience. The University of Texas MD Anderson Cancer Center offers excellent benefits, including medical, dental, paid time off, retirement, tuition benefits, educational opportunities, and individual and team recognition 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 Apply


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