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Postdoctoral In Bayesian Statistics Jobs in New York

OceanX is seeking a Postdoctoral Associate in a field related to marine biology, oceanography ... Conduct bioinformatic and statistical analyses of molecular and ecological datasets. * Contribute ...

Candidates in ABD ("all but dissertation") status will also be considered * Required Knowledge ... statistics mandated by the Clery Act. Click here for a copy of this report.

... in statistics, mathematics, computer science, or a related quantitative field * Deep command of statistical and computational methods: mixed-effects models, longitudinal analyses, Bayesian approaches ...

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

Postdoctoral Research Fellowship Biomedical Data Science The Kontorovich Laboratory, Cardiovascular ... statistical testing and data exploration techniques • Experience working in high-performance ...

... In a Statistics Graduate Level Tutor * Advanced Subject Mastery: Deep knowledge of mathematical statistics, maximum likelihood estimation, sufficient statistics, hypothesis testing theory, Bayesian ...

... In a Statistics Graduate Level Tutor * Advanced Subject Mastery: Deep knowledge of mathematical statistics, maximum likelihood estimation, sufficient statistics, hypothesis testing theory, Bayesian ...

... In a Statistics Graduate Level Tutor * Advanced Subject Mastery: Deep knowledge of mathematical statistics, maximum likelihood estimation, sufficient statistics, hypothesis testing theory, Bayesian ...

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Postdoctoral In Bayesian Statistics information

What is a Postdoctoral position in Bayesian Statistics?

A Postdoctoral position in Bayesian Statistics is a research-focused role for individuals who have recently completed their PhD in statistics, mathematics, or a related field. These positions involve conducting advanced research using Bayesian methods, which apply probability to infer statistical conclusions. Postdocs often work on developing new Bayesian models, collaborating on interdisciplinary projects, and publishing research findings. Such positions are typically temporary and designed to further prepare researchers for academic, industry, or governmental roles.

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

Postdoctoral researchers in Bayesian statistics often encounter challenges such as managing complex, high-dimensional data, staying current with rapidly evolving computational methods, and balancing independent research with collaborative projects. Effective strategies include leveraging open-source statistical software, actively participating in seminars and workshops to stay updated, and establishing regular communication with interdisciplinary teams. Building a strong professional network and seeking mentorship within the department can also help in navigating research obstacles and advancing one's career.

What is the difference between Postdoctoral In Bayesian Statistics vs Postdoctoral In Data Science?

AspectPostdoctoral In Bayesian StatisticsPostdoctoral In Data Science
Required CredentialsPhD in Statistics, Mathematics, or related fieldPhD in Computer Science, Statistics, or related field
Work EnvironmentAcademic research, university labsResearch institutions, tech companies, industry labs
Employer & Industry UsageUniversities, research institutesTech firms, finance, healthcare, consulting
Common Search & Comparison IntentSpecialized research roles in Bayesian methodsBroader data analysis and machine learning roles

Postdoctoral In Bayesian Statistics focuses on advanced research in Bayesian methods within academic settings, requiring deep statistical expertise. In contrast, Postdoctoral In Data Science covers a broader range of data analysis techniques, including machine learning, often in industry environments. Both roles require a PhD but differ in application focus and work environment.

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

To thrive as a Postdoctoral Researcher in Bayesian Statistics, you need an advanced degree (typically a PhD) in statistics or a related field, with strong expertise in Bayesian inference and probabilistic modeling. Proficiency with statistical programming languages such as R, Python, or Stan, and experience with specialized Bayesian analysis software are highly valued. Excellent problem-solving skills, collaboration, and the ability to communicate complex statistical concepts clearly are standout soft skills for this role. These skills and qualities are crucial for conducting rigorous research, publishing impactful results, and contributing effectively to scientific teams.
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Infographic showing various Postdoctoral In Bayesian Statistics job openings in New York as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.
Postdoctoral Associate - Global and Environmental Health

Postdoctoral Associate - Global and Environmental Health

New York University

New York, NY • On-site

$67K - $77K/yr

Full-time

Re-posted 20 days ago


New York University rating

8.3

Company rating: 8.3 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

108th of 555 rated colleges and universities


Job description

Description
Position: Postdoctoral Associate -Postdoctoral Researcher in vaccine modelling, Department of Global and Environmental Health
Department: NYU School of Global Public Health - Global and Environmental Health
Supervisor: Dr. Mark Jit
Employment Dates: September 1, 2026 - April 30, 2027
Schedule: Full-Time
The Department of Global and Environmental Health at the School of Global Public Health, New York University, is seeking applicants for a fully-funded Postdoctoral Researcher position, to lead research across a portfolio of projects related to epidemiological and economic modelling of vaccination. Candidates are expected to have a doctoral degree (ideally PhD/DPhil) in a quantitative subject. They should also have experience in statistical, mathematical, economic or other types of quantitative modeling relevant to health conditions, and relevant computer coding expertise. Candidates with experience in infectious disease modeling and/or cost-effectiveness analysis are of particular interest.
New York University (NYU) is among the highest-ranked private universities in the United States that was identified as a "research powerhouse" by the analytics company Clarivate. The Department of Global and Environmental Health is a growing department with eight full-time faculty who are world leaders in geospatial modelling, infectious disease modelling, economic evaluation and implementation research, the health impact of climate change and environmental pollution, urban health, global health policy and public health entrepreneurship. The position will report to Dr. Mark Jit, the Department chair and faculty lead for the Vaccine Epidemiology and Economics Lab, with a growing portfolio of research funds.
  • The postholder will be responsible for outputs that have the potential to directly inform global (e.g. by the World Health Organization), regional and national vaccine policy-making.
  • The successful candidate will have publication, professional development and global health networking opportunities to prepare them for faculty positions in infectious disease modelling at top universities globally. They will also be part of a growing department that may be creating tenure-track faculty positions in the coming years. The position carries funding to support conference travel, publication fees, meetings with collaborators, and other research-related expenses. The initial appointment is fully funded until March 2027, and is renewable subject to satisfactory progress and availability of funding.

NYU has an extensive global network of teaching and research sites throughout the world. These sites include three portal campuses and 11 global academic centers in Africa, South America, China, Australia, Europe and the Middle East. This unique arrangement allows researchers truly unique opportunities to engage in their research and study around the world; and inform public health practice both locally and globally through the exchange of knowledge.
Applicants must be authorized to work in the United States for the duration of employment
Qualifications
  • Candidates are expected to have a doctoral degree (ideally PhD/DPhil) in a quantitative subject.
  • They should also have experience in statistical, mathematical, economic or other types of quantitative modeling relevant to health conditions, and relevant computer coding expertise.
  • Candidates with experience in infectious disease modeling and/or cost-effectiveness analysis are of particular interest.

Application Instructions
Apply via interfolio
Applications will be reviewed immediately, and the position will remain open until filled.
Any queries about the position may be addressed to mark.jit@nyu.edu.
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is $67,000-$77,000. New York University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as market and organizational considerations when extending an offer.

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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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