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Temporary Machine Learning Postdoc Jobs in Texas

Tamus

Postdoctoral Research Associate

Corpus Christi, TX · On-site

$5K/mo

Documented scholarly achievements in applied statistics, machine learning, or deep learning (e.g ... Funding is temporary, this position is funded for 14-months. * Employment may be impacted by the ...

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Temporary Machine Learning Postdoc information

What are the key skills and qualifications needed to thrive as a Temporary Machine Learning Postdoc, and why are they important?

To thrive as a Temporary Machine Learning Postdoc, you need a PhD in a relevant field, a solid grasp of machine learning theory, and strong programming skills (often in Python or R). Experience with tools such as TensorFlow, PyTorch, and high-performance computing environments, as well as a record of peer-reviewed research, is typically required. Strong analytical thinking, collaboration, and effective communication help you stand out in this research-intensive role. These skills are essential for advancing cutting-edge research, publishing impactful findings, and contributing to interdisciplinary projects.

What types of projects and collaborations can a Temporary Machine Learning Postdoc expect to engage in during their appointment?

A Temporary Machine Learning Postdoc typically works on cutting-edge research projects, often contributing to ongoing studies or initiating novel investigations within the field. Collaboration is common, both within their immediate research group and with interdisciplinary teams, such as data scientists, domain experts, or industry partners. Postdocs may also mentor graduate students, present findings at conferences, and publish papers, gaining valuable experience that can lead to academic or industry roles. The environment is fast-paced and research-driven, offering opportunities for professional growth and expanding one's research portfolio.

What is a Temporary Machine Learning Postdoc?

A Temporary Machine Learning Postdoc is a fixed-term research position, typically held at a university or research institution, focused on advancing knowledge and techniques in machine learning. Postdoctoral researchers in this role work on specific projects, often collaborating with faculty, graduate students, or industry partners. The position is designed to provide advanced training and research experience after earning a PhD, usually lasting from several months to a couple of years. Temporary postdocs may contribute to publishing academic papers, developing algorithms, and mentoring students, while preparing for longer-term academic or industry careers.

What is the difference between Temporary Machine Learning Postdoc vs Data Scientist?

AspectTemporary Machine Learning PostdocData Scientist
CredentialsPhD in Computer Science, Data Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often requires experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageUniversities, research centersBusiness, technology, finance, healthcare
Search & Comparison IntentUnderstanding research-focused roles, academic opportunitiesIndustry roles, applied data analysis, business impact

The Temporary Machine Learning Postdoc is primarily research-oriented, often in academic or research settings, requiring a PhD. In contrast, a Data Scientist typically works in industry, applying data analysis and machine learning to solve business problems, often with a Bachelor's or Master's degree. Both roles involve machine learning skills but differ in environment, focus, and experience level.

What are the most commonly searched types of Machine Learning Postdoc jobs in Texas? The most popular types of Machine Learning Postdoc jobs in Texas are:
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What cities in Texas are hiring for Temporary Machine Learning Postdoc jobs? Cities in Texas with the most Temporary Machine Learning Postdoc job openings:
Temporary Machine Learning Postdoc jobs near you
POSTDOCTORAL RESEARCHER - Data Science and AI Core for Population Research - Xiao Lab [Req#: 9313...

POSTDOCTORAL RESEARCHER - Data Science and AI Core for Population Research - Xiao Lab [Req#: 9313...

UT Southwestern Medical Center

Dallas, TX • On-site

Full-time

Posted 12 days ago

UT Southwestern rating

7.8

Company rating: 7.8 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

101st of 864 rated healthcare providers

Job description

Description
The Postdoctoral Fellow will play a key role in the CPRIT-funded Data Science and AI Core for Population Research (DAICOR), contributing to the development and deployment of advanced imaging-based AI tools to improve early cancer detection and population-level cancer research. Responsibilities include designing and implementing machine learning and deep learning models for medical image analysis across diverse cancer screening modalities (e.g., mammography, CT, ultrasound); developing pipelines for image preprocessing, harmonization, and integration with the DAICOR secure digital platform; and conducting rigorous validation studies to assess performance, bias, and generalizability of AI tools. The fellow will collaborate closely with clinicians, data scientists, and population researchers to extract imaging-derived biomarkers, support multimodal data integration, and contribute to scientific manuscripts and grant reports. Additional duties include assisting with training sessions and providing technical support to healthcare providers and researchers across Texas to facilitate the responsible and effective use of AI tools.
Qualifications
The ideal candidate will have a PhD in biomedical engineering, computer science, medical physics, or a related field, with strong experience in medical image analysis, machine learning, and coding in Python. Experience with large-scale imaging datasets and AI deployment in clinical or research environments is preferred.
Application Instructions
Interested individuals must upload a CV, cover letter, and a list of three references and email Guanghua.Xiao@UTSouthwestern.edu.

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