Data Scientist / Imaging Physics - Research

MD Anderson Cancer Center•Houston, TX

4d•Onsite

About The Position

The University of Texas MD Anderson Cancer Center invites applications for a Data Scientist (Computational Scientist) to join the Surgical Data Science Program within the Institute for Data Science in Oncology (IDSO). IDSO is composed of five major focus areas dedicated to advancing data science and emerging medical technologies to improve clinical care and operational excellence. Within the IDSO focus area on Quality, Safety, and Access, the Surgical Data Science Program brings together experts in data science, systems engineering, and technology development. This multidisciplinary team collaborates closely with surgeons, physicists, and engineers to deliver impactful research and translation in: Multidimensional data analysis (including medical imaging) Predictive modeling Clinical outcomes research Applied machine learning and AI in surgical and perioperative care Shift / hours: Based on business needs and 100% onsite The ideal applicant will have demonstrated experience with/in computing / programming (Python, Matlab, C++, CUDA, Julia, R and/or SQL), machine learning / deep learning methods including neural network design, computer vision / image analysis, and statistical analysis

Requirements

Python, MATLAB, C++, CUDA, Julia, R, and/or SQL
Neural network design and implementation
Computer vision and image analysis
Applied statistics and data modeling
Bachelor's Degree Biomedical Engineering, Electrical Engineering, Computer Engineering, Physics, Applied Mathematics, Science, Engineering, Computer Science, Statistics, Computational Biology, or related field.
3 years Scientific software or industry development/analysis experience.
1 year Required experience with Master's degree.
With PhD, no experience required.

Nice To Haves

Master's Degree Science, Engineering or related field.
PhD Science, Engineering or related field.
SciPy, pandas, statsmodels
OpenCV, XGBoost
PyTorch and/or TensorFlow
SQL or other database querying languages
Regression, clustering, segmentation
Time-series analysis
Recommender systems
Predictive analytics
Bayesian modeling
Data fusion
Supervised and unsupervised learning
Decision trees, A/B testing
Natural language processing (NLP)

Responsibilities

Develop and apply advanced machine learning, deep learning, computer vision, and statistical modeling techniques.
Conduct multidimensional data analyses, including medical image data, clinical data, and outcomes.
Contribute to predictive modeling, decision-support tools, and data-driven clinical insights.
Collaborate with a multidisciplinary team across surgery, physics, engineering, and data science.
Support research translation into clinical workflows and operational improvement initiatives.