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Entry Level Image Processing Scientist Jobs in Texas

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX

$46K - $63K/yr

Dr. Wu has extensive experience on developing and validating image processing methods and image ... D. in one of the natural sciences, computer sciences, applied mathematics, engineering, or related ...

MD Anderson

Postdoc Fellow - Imaging Physics

Houston, TX

$46K - $63K/yr

Dr. Wu has extensive experience on developing and validating image processing methods and image ... D. in one of the natural sciences, computer sciences, applied mathematics, engineering, or related ...

Sarian, Inc.

Sr. Data Scientist

Irving, TX · On-site

Experience with GANs, text-to-image generation, text generation models * Data wrangling ... language processing, and computer vision, tailored to specific needs * Evaluate and compare ...

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Entry Level Image Processing Scientist information

What is the difference between Entry Level Image Processing Scientist vs Entry Level Computer Vision Engineer?

AspectEntry Level Image Processing ScientistEntry Level Computer Vision Engineer
Required CredentialsBachelor's in Computer Science, Electrical Engineering, or related field; knowledge of image processing algorithmsBachelor's in Computer Science, Electrical Engineering, or related field; familiarity with computer vision techniques
Work EnvironmentResearch labs, tech companies, healthcare, or automotive industriesTech companies, robotics, autonomous vehicles, surveillance systems
Employer & Industry UsagePrimarily in research and development roles focusing on image enhancement and analysisDeveloping real-time vision systems, object detection, and scene understanding

Both roles require similar educational backgrounds and work in related industries, but the Image Processing Scientist focuses more on image analysis and enhancement, while the Computer Vision Engineer emphasizes applying algorithms to develop real-time vision applications.

What are some typical projects and collaborative tasks an entry level image processing scientist might work on in their first year?

As an Entry Level Image Processing Scientist, you can expect to work on projects such as developing algorithms for image enhancement, noise reduction, or object detection. You will likely collaborate closely with software engineers, data scientists, and sometimes hardware teams to integrate your solutions into larger systems. Early tasks often include preprocessing data, running experiments, and evaluating algorithm performance. Regular meetings and code reviews are common, helping you learn industry standards and best practices while building valuable teamwork skills.

What does an entry level image processing scientist do?

An Entry Level Image Processing Scientist applies mathematical and computational techniques to analyze, enhance, and interpret digital images. They work with images from various sources such as cameras, satellites, or medical devices, using algorithms and programming to improve image quality or extract useful information. Typical tasks include data preprocessing, implementing image filters, designing and testing computer vision models, and supporting senior scientists in research projects. This role often requires knowledge of programming languages like Python or MATLAB, and familiarity with image processing libraries and tools.

What are the key skills and qualifications needed to thrive as an entry level image processing scientist, and why are they important?

To thrive as an Entry Level Image Processing Scientist, you need a foundation in mathematics, computer science, and image processing concepts, typically supported by a bachelor’s or master’s degree in a relevant field. Proficiency with programming languages such as Python or MATLAB, familiarity with machine learning libraries (like OpenCV, TensorFlow, or PyTorch), and experience with image analysis tools are highly valued. Strong analytical thinking, attention to detail, and effective communication skills help you excel in collaborating with teams and interpreting complex data. These skills are crucial for developing robust image processing solutions, ensuring accuracy, and working effectively within multidisciplinary environments.

What are the most commonly searched types of Image Processing Scientist jobs in Texas?

The most popular types of Image Processing Scientist jobs in Texas are:

What are popular job titles related to Entry Level Image Processing Scientist jobs in Texas?

For Entry Level Image Processing Scientist jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Entry Level Image Processing Scientist jobs in Texas look for?

The top searched job categories for Entry Level Image Processing Scientist jobs in Texas are:

What cities in Texas are hiring for Entry Level Image Processing Scientist jobs?

Cities in Texas with the most Entry Level Image Processing Scientist job openings:

Entry Level Image Processing Scientist jobs near you

Postdoc Fellow - Imaging Physics

MD Anderson

Houston, TX

$46K - $63K/yr

Full-time

Re-posted 23 days ago

MD Anderson Cancer Center rating

8.4

Company rating: 8.4 out of 10

Based on 170 frontline employees who took The Breakroom Quiz

23rd of 887 rated healthcare providers

Job description

A postdoctoral fellowship position is available in the Department of Imaging Physics in the laboratory of Chengyue Wu, PhD. Dr. Chengyue Wu's research interests focus on computational precision oncology, especially integrating computational/mathematical approaches with emerging biomedical imaging techniques to improve the diagnosis, prognosis, and treatment of human cancers. Dr. Wu has extensive experience on developing and validating image processing methods and image-guided models for investigating tumor growth and treatment response, tumor-associated vasculature and microenvironment, and drug delivery. The lab is in a highly collaborative research environment with access to world-class resources, expertise, and data. Current projects seeking postdoctoral fellows include:
Image-guided computational modeling ("digital twins") to predict and optimize cancer (especially breast cancer) treatment response on a patient-specific basis.
Development of deep learning models, longitudinal image analysis, and multi-modality data integration to improve breast cancer early detection.
LEARNING OBJECTIVES
This postdoctoral fellow will engage in highly productive interdisciplinary research projects in image-guided precision oncology and personalized cancer healthcare. The fellow will expand their knowledge and skills in quantitative imaging, image analysis, artificial intelligence (AI)/deep learning technologies, mathematical biomechanical modeling, inverse problems, and uncertainty quantification. The fellow will have opportunities to contribute to ongoing research projects and will be encouraged to explore and develop new areas of research interest with guidance from the mentor. The fellow will be expected to work closely with research/clinical collaborators, communicate findings via reports, abstracts, presentations, and publications, and actively participate in seminars, conferences, and related academic endeavors.
ELIGIBILITY REQUIREMENTS
Applicants should have earned a Ph.D. in one of the natural sciences, computer sciences, applied mathematics, engineering, or related fields or a medical degree. Experience with machine learning and deep learning techniques, mathematical modeling, or medical image analysis is preferred. Applicants do not need to be US citizens or permanent residents. This appointment is not part of a clinical training program; individuals holding an M.D. degree or equivalent are not permitted to engage in patient care activity.
ADDITIONAL APPLICATION INFORMATION
The trainee will be appointed for one year from the date of hire with an option to be renewed for up to three years.
POSITION INFORMATION
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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Dr. Chengyue Wu

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