Postdoctoral Research Scientist

Montana State University; Bozeman, Northern (MT, KY); Hybrid; USD 55,000 - 75,000; Full time

Job summary

Montana State University’s Department of Land Resources & Environmental Sciences invites applications for a Research Professional to advance a DOE EPSCoR project in soil science and biogeochemistry. The role focuses on developing the Soil Functional Type framework, harmonizing datasets, and mapping biogeochemical processes to inform Earth system models.

The candidate will collaborate with national laboratories, have ML/R/Python proficiency, and support field work in Montana.

Qualifications

• PhD in soil science, biogeochemistry, environmental data science, Earth system modeling, or a related field.
• Experience applying statistical or machine learning methods to environmental or geospatial datasets.
• Proficiency in a scientific programming language (R or Python).
• Experience working with large environmental or soil datasets.
• Demonstrated experience with written and oral scientific communication.
• Experience with unsupervised machine learning methods.
• Experience with Earth System Models (e.g., E3SM/ELM) or land surface/biogeochemical modeling.
• Background in soil biogeochemistry, mineralogy, or soil organic matter dynamics.
• Prior experience collaborating with national laboratories or large multi-institutional research teams.

Responsibilities

• Soil Functional Type (SFT) Framework Development: Compile and harmonize global observational soil databases and apply unsupervised ML to develop depth-explicit SFTs.
• Biogeochemical Representativeness Analysis & SFT Mapping: Evaluate sample coverage and produce global SFT maps identifying data gaps.
• Field Campaign Support: Provide analytical/logistical support for Montana field sampling and integrate field data into SFT validation.
• Lead benchmarking activities with Dr. Avni Malhotra (PNNL) and diagnose Earth System Model limitations.
• Complete an extended residency at PNNL and contribute to EMSL proposal development.

Skills

PhD in Soil Science

ML/Statistics

R or Python

Large datasets

Scientific communication

Education

PhD in related field

Tools

R

Python

Job description

Please see Special Instructions for more details.

This position is not eligible for new sponsorship.

Position Information

Announcement Number

STAFF - VA - 27112

Position Number

4C7717

Department

Land Resources & Environ Sci

Division

College of Agriculture/MAES

Appointment Type

Research Professional

Contract Term

Fiscal Year

FLSA

Exempt

Union Affiliation

Exempt from Collective Bargaining

FTE

1.0

Salary

$65,000 annually, commensurate with experience, education, and qualifications.

Contract Type

LOA

Recruitment Type

Open

General Statement

The Department of Land Resources and Environmental Sciences ( LRES ) at Montana State University conducts research and teaching across soil science, ecology, hydrology, and natural resource management. This position supports a newly funded DOE Established Program to Stimulate Competitive Research (EPSCoR) project led by PI Dr. Sophie von Fromm, in partnership with Pacific Northwest National Laboratory and Lawrence Livermore National Laboratory.

Duties and Responsibilities

• Soil Functional Type ( SFT ) Framework Development
  • Compile and harmonize global observational soil databases in support of SFT framework development.
  • Apply (unsupervised) machine learning methods to develop depth-explicit SFTs.
• Biogeochemical Representativeness Analysis & SFT Mapping
  • Evaluate whether existing global soil databases adequately sample the biogeochemical process space relevant to soil organic matter ( SOM ) dynamics.
  • Produce global SFT maps and identify priority data/sampling gaps.
• Field Campaign Support
  • Provide analytical and logistical support for a Montana field sampling campaign.
  • Integrate field-collected data (reactive mineralogy, radiocarbon, SOM fractionation) into SFT validation.
• Lead benchmarking activities in close collaboration with Dr. Avni Malhotra ( PNNL ).
• Diagnose where current Earth System Model structures fail to represent mineral-organic matter controls on carbon persistence.
• Complete an extended research residency at PNNL ; contribute to development of an EMSL user proposal for molecular-scale characterization.

Required Qualifications – Experience, Education, Knowledge & Skills

• PhD in soil science, biogeochemistry, environmental data science, Earth system modeling, or a related field.
• Demonstrated experience applying statistical or machine learning methods to environmental or geospatial datasets.
• Proficiency in a scientific programming language (R or Python).
• Experience working with large environmental or soil datasets.
• Demonstrated experience with written and oral scientific communication.

Preferred Qualifications – Experience, Education, Knowledge & Skills

• Experience with unsupervised machine learning methods.
• Experience with Earth System Models (e.g., E3SM/ ELM ) or land surface/biogeochemical modeling.
• Background in soil biogeochemistry, mineralogy, or soil organic matter dynamics.
• Prior experience collaborating with national laboratories or large multi-institutional research teams.

The Successful Candidate Will

• Ability to work independently and manage multiple concurrent project objectives.
• Strong collaborator across disciplines, institutions, and remote research teams.
• Detail-oriented and highly organized, with strong data management practices.
• Adaptable to both computational/lab-based work and field-based research settings.

Position Special Requirements/Additional Information

• Position is contingent upon continued DOE EPSCoR grant funding.
• Requires an extended research residency at Pacific Northwest National Laboratory (Richland, WA).
• Occasional travel to Lawrence Livermore National Laboratory and Montana field sites required.
• Occasional travel to national scientific conferences (e.g., AGU ) required.

Physical Demands

Most work is computer-based. Field campaign support may require traversing uneven outdoor terrain, digging and soil sampling, and transporting up to 40 lbs, with exposure to variable weather conditions.
To perform this job successfully, an individual must be able to perform each essential duty satisfactorily with or without reasonable accommodations. The requirements listed above are representative of the knowledge, skill, and/or ability required.

This position has supervisory duties?

No

Number of Vacancies

1

Special Instructions

This position is not eligible for new sponsorship.

EEO Statement

Montana State University is an equal opportunity employer. MSU does not discriminate against any applicant on the basis of race, color, religion, creed, political ideas, sex, sexual orientation, gender identity or expression, age, marital status, national origin, physical or mental disability, or any other protected class status in violation of any applicable law.
In compliance with the Montana Veteran's Employment Preference Act, MSU provides preference in employment to veterans, disabled veterans, and certain eligible relatives of veterans. To claim veteran's preference, please complete the veteran's preference information located in the Demographics section of your profile.

Supplemental Questions

Required fields are indicated with an asterisk (*).