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Research Machine Learning Federated Learning Jobs in Gainesville, FL

Varsity Tutors

Machine Learning Tutor

Gainesville, FL · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

University of Florida

Post Doc Associate

Gainesville, FL · On-site

$61K - $65K/yr

Working experience with large language models, data science using EHRs, machine learning, data ... Implement methods into software that meets research needs, manage and update source codes as needed.

Santa Fe College

eLearning Director

Gainesville, FL · On-site

$74K/yr

The ideal candidate will have demonstratable knowledge of best practices, current research, and innovations in eLearning, instructional design, and academic technologies as well as a strong ...

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All JobsResearch Machine Learning Federated Learning JobsResearch Machine Learning Federated Learning Jobs in Gainesville, FL

Research Machine Learning Federated Learning information

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$23.1K

$38.6K

$79.7K

How much do research machine learning federated learning jobs pay per year?

As of Aug 25, 2026, the average yearly pay for research machine learning federated learning in Gainesville, FL is $38,581.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,400.00 and $41,700.00 per year, depending on experience, location, and employer.

What is a researcher in machine learning federated learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What are the key skills and qualifications needed to thrive as a researcher in machine learning federated learning?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

What job categories do people searching Research Machine Learning Federated Learning jobs in Gainesville, FL look for?

The top searched job categories for Research Machine Learning Federated Learning jobs in Gainesville, FL are:

What cities near Gainesville, FL are hiring for Research Machine Learning Federated Learning jobs?

Cities near Gainesville, FL with the most Research Machine Learning Federated Learning job openings:

Research Machine Learning Federated Learning jobs near you

Post Doctoral Associate

University of Florida

Gainesville, FL • On-site

$44K - $60K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

University Of Florida rating

7.2

Company rating: 7.2 out of 10

Based on 108 frontline employees who took The Breakroom Quiz

385th of 622 rated colleges and universities

Job description

Post Doctoral Associate
Job no: 540937
Work type: Post Doc Associate
Location: Main Campus (Gainesville, FL)
Categories: Health Care Administration/Support
Department:29130100 - MD-RADIOLOGY-ADMINISTRATION
Classification Title:
Post Doc Associate
Classification Minimum Requirements
Ph.D. in biomedical informatics, computer science, data science, statistics, or related STEM fields.
Job Description:
The AI Postdoctoral Fellow supports the Department of Radiology's research laboratory by designing and conducting advanced artificial intelligence research in medical imaging. This position focuses on developing clinically meaningful machine learning models, publishing research in high-impact peer-reviewed journals, collaborating with physician-scientists, and advancing translational and grant-funded innovation across the department's research priorities.
Key responsibilities include:
  • Conduct independent and collaborative artificial intelligence research in medical imaging.
  • Develop novel machine learning and deep learning methods for clinical, research, and educational applications in radiology.
  • Build, train, validate, and optimize AI/ML models using CT, MRI, PET, chest X-ray, and multimodal datasets.
  • Preprocess and manage large-scale clinical imaging data, including DICOM and NIfTI files, with careful attention to data integrity, reproducibility, privacy, and regulatory compliance.
  • Perform rigorous model evaluation, including external validation, robustness testing, and bias and fairness assessments.
  • Lead manuscript preparation and present research findings through peer-reviewed journals and national conferences, including RSNA, MICCAI, SIIM, and ISMRM.
  • Support grant proposal development by contributing technical aims, preliminary data, methodological expertise, and innovation narratives.
  • Mentor junior trainees, including students, residents, and research assistants, and actively participate in laboratory meetings and collaborative research initiatives.
  • Develop and maintain well-documented, reproducible AI pipelines using version control, experiment tracking, and other established best practices.

Expected Salary:
Salary is commensurate with NIH Guidelines
Required Qualifications:
Ph.D. in biomedical informatics, computer science, data science, statistics, or related STEM fields.
Preferred
  • Demonstrated experience developing machine learning models, preferably for healthcare or medical imaging applications.
  • Strong record of scholarly research, including peer-reviewed publications.
  • Experience translating imaging AI into clinical practice, including workflow integration or deployment.
  • Experience working with large-scale or multicenter datasets, such as NIH, UK Biobank, or OSIC.
  • Specialized expertise in emerging areas such as foundation models, self-supervised learning, federated learning, explainable AI, or multimodal data fusion.
  • Understanding of academic medicine and demonstrated potential for long-term leadership in translational AI research.

Special Instructions to Applicants:
In order to be considered, you must upload your cover letter and most recent CV.
Application must be submitted by 11:55 p.m. (ET) of the posting end date.
Health Assessment Required:No
Advertised: 13 Aug 2026 Eastern Daylight Time
Applications close: 24 Aug 2026 Eastern Daylight Time
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About University of Florida

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The University of Florida is one of the top ranked public universities in the United States (ranked top 5 amongst public universities in 2023 US news and world report). It is one of only a few comprehensive universities, having medical, veterinary, dental, nursing, public health, and engineering disciplines all co-localized on the same, contiguous campus to facilitate interdisciplinary collaboration. Gainesville is located in the northern region of Florida, within 1-1.5 hours of each coast, and just 1.5-2 hours to Orlando and Tampa. It is a small to medium-sized city with a low cost of living, excellent public and private schools, and southern hospitality. While Gainesville is widely recognized as the home of the Gators, it is quickly becoming known as a center for innovation and a place with a lifestyle that's comfortable for families, yet attractive for young professionals.

Industry

Colleges, universities, and professional schools

Company size

5,001 - 10,000 Employees

Headquarters location

Gainesville, FL, US

Year founded

1853

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