UT MD Anderson→
Research Intern - Translational Molecular Pathology
InternshipOn-site
Location
Houston, TX
Salary
Not listed
Experience
Not specified
Posted
1 week ago
Skills
artificial intelligencecomputational methodsmultimodal pathologypythonimage processingdeep learningscientific software developmentdata integrationdata analysiscomputational infrastructureanalytic pipelines
Job Description
Summary: UT MD Anderson is a leading cancer research institution, and they are seeking a research intern in the department of Translational Molecular Pathology. The role involves developing and implementing innovative AI tools for multimodal pathology data, collaborating with pathologists and clinicians to address clinical challenges.
Responsibilities:
- Develop impact-driven AI technologies for pathology
- Develop and maintain computational methods with AI in multimodal pathology
- Work with a highly interdisciplinary team to generate biologically meaningful results and work towards clinical translation of AI for oncology
- Keep current and evaluate state-of-the-art methods and tools, establish and help maintain computational infrastructure and analytic pipelines
- Present results in collaboration meetings, internal and external conferences
Required Qualifications:
- Applicant must hold a bachelor's or master's degree
- Degree must have been obtained recently (within one year)
- Applicant must have previous research experience
- Applicants who hold a Ph.D. or equivalent doctoral degree (e.g., M.D., D.V.M., M.B.B.S.) are not eligible
- Ideal candidates will have a minimum of a bachelor's degree in electrical engineering, Computer Science, Physics, Applied Mathematics, Biomedical Engineering, Statistics, Computational Biology, or related field
- Extensive experience in scientific software development/analysis (specifically in Python, image processing and Deep Learning)
Required Skills: Artificial Intelligence, Computational Methods, Multimodal Pathology, Python, Image Processing, Deep Learning, Scientific Software Development, Data Integration, Data Analysis, Computational Infrastructure, Analytic Pipelines