Research Scientist, Spatial Statistics

The International Society for Bayesian Analysis; Oak Ridge (TN); On-site; USD 80,000 - 120,000; Full time

Job summary

An esteemed research institution is seeking a Research Scientist for its Spatial Statistics Group in Oak Ridge, TN. The ideal candidate will develop advanced statistical and machine-learning methods to tackle real-world challenges in dynamic population estimation and infrastructure resilience. Candidates should hold a Ph.D. in a relevant field and possess strong programming skills in Python or R, along with knowledge of spatial data techniques. Join a versatile team and contribute to impactful research and mentoring opportunities.

Qualifications

• Ph.D. or equivalent experience in Statistics, Applied Math, Computer Science, or related fields.
• Practical knowledge of spatial/spatio-temporal data and probabilistic modeling.
• Proficiency in programming languages like Python or R.

Responsibilities

• Develop and apply advanced statistical and machine-learning methods.
• Construct scalable, HPC-enabled workflows for various analytics tasks.
• Engage with a diverse team and contribute through publications.

Skills

Statistical modeling

Machine learning

Programming in Python

Programming in R

Data analysis

Education

Ph.D. in Statistics, Applied Math, or Computer Science

Job description

Exciting opportunity at Oak Ridge National Laboratory! Our Spatial Statistics Group is looking for a Research Scientist to join us in Oak Ridge, TN.

As part of our team, you will:
– Develop and apply advanced statistical and machine-learning methods for real-world spatio-temporal challenges.
– Construct scalable, HPC-enabled workflows covering dynamic population estimation, infrastructure resilience, and transportation analytics.
– Engage with a diverse team of statisticians, data scientists, and domain experts.
– Contribute through publications, conference presentations, and mentoring of junior colleagues.

We are looking for a candidate with:
– A Ph.D. or equivalent experience in Statistics, Applied Math, Computer Science, or related fields.
– Practical knowledge of spatial/spatio-temporal data and probabilistic modeling (e.g., Bayesian or nonparametric techniques).
– Proficiency in programming languages like Python, R, or similar, and familiarity with high-performance computing.
– A drive to simplify complex methodologies into actionable insights.

If you are passionate about exploration, enjoy solving intricate data challenges, and aspire to address national-scale issues, we invite you to apply.

Explore more and submit your application: https://jobs.ornl.gov/job/Oak-Ridge-Research-Scientist%2C-Spatial-Statistics-TN-37830/1309019000/

For inquiries or to recommend a suitable candidate, feel free to get in touch!