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MISSION STATEMENT The mission of The University of Texas M. D. Anderson Cancer Center is to eliminate cancer in Texas...

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Data Scientist Cancer Systems Imaging

MD Anderson Cancer Center Houston, TX, US

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$106k - $159k · Senior Full-time Posted 23 days ago 6 min read

MISSION STATEMENT

The mission of The University of Texas M. D. Anderson Cancer Center is to eliminate cancer in Texas, the nation, and the world through outstanding programs that integrate patient care, research and prevention, and through education for undergraduate and graduate students, trainees, professionals, employees and the public.

SUMMARY

The Research Scientist will lead and support advanced neuroimaging research aimed at investigating structural and functional brain changes in cancer populations. This includes breast cancer patients experiencing chemotherapy-related cognitive impairment ("chemo brain"), individuals with neurofibromatosis type 1 (NF1), patients with head and neck cancers, and individuals with brain tumors. The overarching goal is to identify imaging biomarkers and brain-behavior relationships that inform clinical outcomes, therapeutic response, and long-term survivorship. The scientist will utilize and integrate multi-modal neuroimaging techniques-such as structural MRI, diffusion tensor imaging (DTI), and both resting-state and task-based functional connectivity-with behavioral, cognitive, and clinical data. Emphasis is placed on quantitative image analysis, advanced statistical modeling, and robust data infrastructure to enable reproducible, translational research that improves understanding of cancer-related neurotoxicity and neurological dysfunction. This position offers the opportunity to contribute to high-impact, interdisciplinary research while supporting data-driven clinical advancements in cancer neuroscience.

Shift / Hours: Monday - Friday / 8am - 5pm / Hybrid: 80% onsite and 20% remote in Texas

The ideal candidate is a highly motivated computational imaging scientist with strong expertise in clinical neuroimaging, statistical modeling, and multimodal neuroimaging data analysis. They bring advanced training in neuroscience and computational biology and have demonstrated experience developing reproducible pipelines, integrating structural, functional and diffusion MRI data with clinical and behavioral variables, and performing quantitative image analysis. The candidate should have a proven record of applying machine learning, statistical modeling, and software tool development to support translational neuroimaging research and works effectively in multidisciplinary scientific teams.

JOB SPECIFIC COMPETENCIES

Algorithm Development for Quantitative Imaging (Weight 30%):

Design, implement, and optimize novel algorithms for the quantitative analysis of medical imaging data such as MRI, PET, and CT scans. Employ advanced techniques including signal processing, statistical modeling, and AI/ML to extract imaging biomarkers associated with tumor biology, disease progression, and therapeutic response. Collaborate with domain experts to refine algorithmic outputs for translational and clinical applications.

Multimodal Data Integration and Analysis (Weight 20%):

Analyze and integrate high-dimensional datasets from various sources including radiologic imaging, genomics, transcriptomics, pathology, and clinical metadata. Develop standardized and reproducible pipelines to preprocess, harmonize, and combine datasets. Apply statistical and computational methods to identify meaningful patterns and correlations across data modalities that inform hypotheses and clinical strategies.

Software Tool Development and Maintenance (Weight 10%):

Develop, test, and maintain customized software tools and pipelines that support automated and interactive image analysis workflows. Build user-friendly applications and command-line tools for tasks such as image segmentation, radiomics feature extraction, data annotation, and batch processing. Ensure that tools are robust, scalable, and adaptable for use in ongoing and future projects.

Deep Learning and Machine Learning Applications (Weight 10%):

Apply deep learning (e.g., CNNs, autoencoders) and traditional machine learning methods (e.g., SVM, random forest, gradient boosting) to build predictive and classification models using imaging and other biomedical data. Perform model training, evaluation, hyperparameter tuning, and interpretability analysis. Ensure reproducibility through standardized pipelines and collaborative model development practices.

Image Processing and Visualization (Weight 10%):

Implement image preprocessing steps including normalization, denoising, spatial registration, and segmentation of regions of interest. Generate high-quality static and interactive visualizations (e.g., heatmaps, overlays, 3D renderings) to communicate findings and highlight patterns in imaging or multimodal datasets. Work with scientific and clinical collaborators to design visual outputs that aid interpretation and decision-making.

Collaboration with Scientific and Clinical Teams (Weight 4%):

Work in close collaboration with imaging scientists, oncologists, radiologists, and researchers to understand scientific goals and tailor computational strategies accordingly. Participate in multidisciplinary team meetings, contribute to experimental design, and provide analytical input. Assist in translating computational results into insights suitable for manuscripts, grants, and clinical applications.

Documentation and Reporting (Weight 4%):

Maintain comprehensive and well-organized documentation for all analytical pipelines, codebases, and research outputs. Prepare clear data summaries, methods descriptions, and technical figures for inclusion in manuscripts, presentations, and lab reports. Contribute to code repositories with version-controlled updates and standardized usage instructions.

Data Management and Infrastructure Support (Weight 4%):

Support data organization and management across the lab's imaging and biomedical datasets. Assist in configuring storage solutions and computation infrastructure (e.g., cloud platforms, high-performance computing clusters). Ensure compliance with data privacy and security protocols and institutional policies governing patient data and research integrity.

Quality Assurance and Reproducibility (Weight 4%):

Implement quality control processes for data inputs, model outputs, and system performance. Use reproducibility tools such as Git for code versioning, Conda or Docker for environment management, and workflow automation tools like Snakemake or Nextflow. Validate reproducibility across different datasets and analysis scenarios.

Professional Development and Training (Weight 4%):

Engage in ongoing learning and skill development in computational imaging, AI/ML, and biomedical informatics. Attend conferences, seminars, and training workshops. Mentor lab members and provide informal or formal training sessions on relevant computational tools, programming practices, and data analysis strategies.

Other duties as assigned

EDUCATION

Required: Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.
Preferred: Master's Degree Science, Engineering or related field.
Preferred: PhD Science, Engineering or related field.

WORK EXPERIENCE

Required: 3 years Scientific software or industry development/analysis experience. or
Required: 1 year Required experience with Master's degree. or Required: With PhD, no experience required.

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.

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

Additional Information

Requisition ID: 177250
Employment Status: Full-Time
Employee Status: Regular
Work Week: Days
Minimum Salary: US Dollar (USD) 106,500
Midpoint Salary: US Dollar (USD) 133,000
Maximum Salary : US Dollar (USD) 159,500
FLSA: exempt and not eligible for overtime pay
Fund Type: Soft
Work Location: Onsite
Pivotal Position: Yes
Referral Bonus Available?: No
Relocation Assistance Available?: Yes

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