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Trainee Python R Jobs (NOW HIRING)

Postdoctoral Fellow

Chapel Hill, NC · On-site

$41K - $56K/yr

... and trainees from highly diverse backgrounds to create a socially responsible, highly skilled ... Knowledge of Python or R is preferred. Ability to analyze multi-omic data, including microbiome ...

Postdoctoral Fellow

Chapel Hill, NC

$41K - $56K/yr

... and trainees from highly diverse backgrounds to create a socially responsible, highly skilled ... Knowledge of Python or R is preferred. Ability to analyze multi-omic data, including microbiome ...

Postdoctoral Fellow

Chapel Hill, NC

$41K - $56K/yr

... and trainees from highly diverse backgrounds to create a socially responsible, highly skilled ... Knowledge of Python or R is preferred. Ability to analyze multi-omic data, including microbiome ...

Postdoctoral Fellow

Chapel Hill, NC · On-site

$41K - $56K/yr

... and trainees from highly diverse backgrounds to create a socially responsible, highly skilled ... Knowledge of Python or R is preferred. Ability to analyze multi-omic data, including microbiome ...

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How much do trainee python r jobs pay per year?

As of Jun 5, 2026, the average yearly pay for trainee python r in the United States is $139,971.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $164,500.00 per year, depending on experience, location, and employer.
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Postdoctoral Fellow - Biostatistics

Postdoctoral Fellow - Biostatistics

MD Anderson Cancer Center

Houston, TX • On-site

$64K - $76K/yr

Full-time

Medical, Dental, Retirement, PTO

Posted 28 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

32nd of 865 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

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