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Postdoctoral In Bayesian Deep Jobs (NOW HIRING)

EVOZYNE INC

Applied AI Research Fellow

Chicago, IL · On-site

Late-stage PhD student or postdoc in a quantitative or computational field * Hands-on experience ... Familiarity with modern machine learning approaches (e.g., deep learning, generative models, or ...

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How much do postdoctoral in bayesian deep jobs pay per year?

As of Jun 7, 2026, the average yearly pay for postdoctoral in bayesian deep in the United States is $59,022.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,000.00 and $66,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by postdoctoral researchers specializing in Bayesian deep learning, and how can they be addressed?

Postdoctoral researchers in Bayesian deep learning often encounter challenges such as managing the complexity of probabilistic models, computational resource limitations, and staying updated with rapid advancements in the field. Collaborating closely with interdisciplinary teams and leveraging cloud-based computing resources can help address these hurdles. Additionally, actively participating in academic conferences and workshops is crucial for keeping abreast of new methodologies and establishing valuable professional connections.

What are the key skills and qualifications needed to thrive as a Postdoctoral Researcher in Bayesian Deep Learning, and why are they important?

To thrive as a Postdoctoral Researcher in Bayesian Deep Learning, you need a PhD in computer science, statistics, or a related field with expertise in probabilistic modeling and deep learning techniques. Proficiency in programming languages such as Python, experience with deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with Bayesian inference methods are essential. Strong analytical thinking, problem-solving abilities, and effective scientific communication set candidates apart. These skills and qualities are crucial for advancing research, publishing impactful work, and contributing to innovative solutions in the field.

What is the difference between Postdoctoral In Bayesian Deep vs Postdoctoral In Machine Learning?

AspectPostdoctoral In Bayesian DeepPostdoctoral In Machine Learning
Required CredentialsPhD in Computer Science, Data Science, or related fields; expertise in Bayesian methods and deep learningPhD in Computer Science, Data Science, or related fields; strong background in machine learning algorithms
Work EnvironmentResearch labs, academia, industry R&D teams focusing on probabilistic models and deep neural networksResearch labs, academia, industry R&D teams working on various machine learning applications
Employer & Industry UsageUniversities, tech companies, AI research institutes emphasizing Bayesian approachesUniversities, tech companies, AI research institutes focusing on broad machine learning techniques

Postdoctoral In Bayesian Deep positions focus on probabilistic models and deep learning with Bayesian methods, while Postdoctoral In Machine Learning covers a broader range of algorithms and techniques. Both roles require advanced research skills and often overlap in industry and academia, but Bayesian Deep roles emphasize probabilistic reasoning within deep neural networks.

What is a Postdoctoral Researcher in Bayesian Deep Learning?

A Postdoctoral Researcher in Bayesian Deep Learning is a scholar who has completed their PhD and is conducting advanced research in the intersection of Bayesian statistics and deep learning models. Their work often involves developing probabilistic machine learning methods that incorporate uncertainty estimation into neural networks. These researchers aim to improve the reliability, interpretability, and robustness of deep learning systems for applications in fields such as computer vision, natural language processing, and healthcare. Their roles typically include publishing research papers, collaborating with other scientists, and sometimes mentoring students.
[EOI][SPRING 2026] Polymathic AI Postdoctoral Researcher

[EOI][SPRING 2026] Polymathic AI Postdoctoral Researcher

New York University

New York, NY • On-site

$80K - $110K/yr

Full-time

Posted 7 days ago

New York University rating

8.3

Company rating: 8.3 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

94th of 534 rated colleges and universities

Job description

Description
The Center for Data Science at New York University (NYU) invites applications for postdoctoral scholars as part of the Polymathic AI initiative
Polymathic AI is inviting applications for postdoctoral researchers in our team. Our research focuses on building and understanding foundation models for science, and in particular modeling complex interconnected systems from astronomy, biology, fluid dynamics to solar physics. For this position, we are looking for postdoctoral researchers that will contribute to our research on interpretability, generalization and general understanding of foundation models. The overarching objective is to create open access tools that enable researchers to reach meaningful understanding of the complex model quickly thus speeding up the pace of scientific discovery.
Fulfilling this objective requires creativity to combine core-principles of machine learning to the practical tools of deep learning, now available through modern foundation models. For the theory part, the selected candidate will work in close collaboration with the Adaptive Bayesian Intelligence group headed by Dr. Emtiyaz Khan at RIKEN-AIP (in Tokyo, Japan) and TU Darmstadt (in Germany). The candidate is expected to make the best use of adaptive-learning methods to develop practical tools to the most pressing scientific challenges in science. The collaboration may require some amount of travelling to Japan and Germany.
The selected candidates will join a vibrant, interdisciplinary team based in New York, spanning NYU and the Flatiron Institute, composed of machine learning researchers, engineers, and domain scientists. This collaborative environment at Polymathic AI offers a unique opportunity to work on cutting edge AI models and advance AI for scientific discovery.
Several positions are available. The review of applications will begin immediately and will continue until the positions are filled.
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is $80,000-$110,000.
Qualifications
We are seeking highly motivated individuals with backgrounds in computer science, machine learning, and science to join our group in a quest to perform breakthrough research. An ideal candidate has strong research skills in relevant areas: machine learning, foundation models, computational sciences. A Ph.D. degree is required. Significant experience with programming, project management, and large-scale model training is a plus.
Application Instructions
To apply, please send us your application and reference letters:
  • The application should include:
    • A 1-2 page research statement, please make sure to address the following:
      • the specific areas you want to work on,
      • how they fit with research in Polymathic,
      • how they build upon your previous work, and
      • your preferred start date;
    • Your current CV with research background and a list of your publications;
    • Copies of your two representative publications.
  • Submit the application to LINK. We encourage you to also include links to any software that you have developed.
  • Arrange for two letters of reference from your previous research supervisors and collaborators to be sent directly within 2 weeks of your submission.

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About New York University

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Since its founding in 1831, NYU has been an innovator in higher education, reaching out to an emerging middle class, embracing an urban identity and professional focus, and promoting a global vision that informs its 20 schools and colleges. Today, that trailblazing spirit makes NYU one of the most prominent and respected research universities in the world, featuring top-ranked academic programs and accepting fewer than one in eight undergraduates. Anchored in New York City and with degree-granting campuses in Abu Dhabi and Shanghai as well as 12 study away sites throughout the world, NYU is a leader in global education, with more international students and more students studying abroad than any other US university.

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