Title: Research Scientist 3 Location: Albuquerque United States Job Description: Requisition ID req36433 Working Title Research Scientist 3 Position Grade 13 Position Summary The FOR-NM Project (Forest Research for New Mexico Water and Carbon Management) seeks applications for a Research Scientist 3 position with a focus on data management. We are looking for a motivated and organized person with a background (MS degree preferred) in ecology, data analytics, remote sensing, GIS, and/or hydrology to join our team. This multi-institutional research program spans five institutions across the state of New Mexico including collaboration with Sandia National Laboratory. The project aims to improve management of New Mexico's forested watersheds by addressing key gaps in understanding of water and carbon dynamics in relation to forest management. Duties include collating and managing data with version-controlled programmatic workflows in R and/or Python, including large volumes of high-frequency sensor data and model outputs; working with investigators to design and deliver data products to open access repositories; and training participants to track and quality control data. Interest in participating in field work as approximately 15% of duties is strongly desired. Expertise in working with environmental sensor data and geospatial data (including remote sensing products) is required. This position will be based at the University of New Mexico in Albuquerque, NM. Partial but not fully remote work options can be considered for exceptional candidates. The position will start as soon as possible and will be hired on a 1-year contract, with the expectation of renewal for additional years pending satisfactory performance. The position's online application is open and applications will be reviewed on a rolling basis. See the Position Description for additional information. Conditions of Employment - Successful candidate must submit to a post-offer, pre-employment physical examination and medical history check. Additional health screenings may be required, dependent on the nature of the research conducted, as determined by Employee Occupational Health Services. Minimum Qualifications Bachelor's degree; at least 3 years of experience directly related to the duties and responsibilities specified. Completed degree(s) from an accredited institution that are above the minimum education requirement may be substituted for experience on a year for year basis. Preferred Qualifications - Masters in ecology, data analytics, remote sensing, GIS, hydrology, or closely related field - Previous experience working with large datasets - Experience working collaboratively with a team of scientists across multiple institutions - Experience with numerical modeling, remote sensing, and/or environmental sensors - Excellent English verbal communication skills - Experience with programming in R and/or Python, and collaborative version-controlled workflows including Git and/or Jupyter Notebooks - Experience with developing data processing pipelines using R and/or Python Additional Requirements Campus Main - Albuquerque, NM Department AS Biology General Administrative (048F) Employment Type Staff Staff Type Term - Full-Time Term End Date 1 year from start date Status Exempt Pay Monthly: $4,236.27 - $5,950.53 Benefits Eligible This is a benefits eligible position. ERB Statement As a condition of employment, eligible employees working greater than .25 FTE as determined by the New Mexico Education Retirement Act must make mandatory retirement contributions. For more information, review the Benefits Eligibility at a Glance grid. Background Check Required Yes For Best Consideration Date 5/7/2026 Eligible for Remote Work Yes Eligible for Remote Work Statement This position is eligible for a remote work agreement (RWA), to include Hybrid. Application Instructions Only applications submitted through the official UNMJobs site will be accepted. If you are viewing this job advertisement on a 3rd party site, please visit UNMJobs to submit an application. Please submit a resume and cover letter with UNMJobs application. Positions posted with a Staff Type of Regular or Term are eligible for the Veteran Preference Program. See the Veteran Preference Program webpage for additional details. The University of New Mexico is committed to hiring and retaining a diverse workforce. We are an Equal Opportunity Employer, making decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability, or any other protected class. The University of New Mexico requires all regular staff positions successfully pass a pre-employment background check. This may include, but is not limited to, a criminal history background check, New Mexico Department of Health fingerprint screening, New Mexico Children, Youth, and Families Department fingerprint screening, verification of education credentials, and/or verification of prior employment.

Role Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Quantitative Biology Expert Type: Contract Compensation: $85–$95/hour Location: Remote Commitment: 20 hours/week Role Responsibilities - Author and review technical tasks to evaluate AI model performance on quantitative biology problems. - Produce original problem sets grounded in: - sequence alignments - phylogenetic trees - expression heatmaps - pathway figures - Write reference solutions and apply structured quality checks to ensure task accuracy. - Collaborate with AI research teams to improve training data quality and downstream performance. - Work independently and asynchronously with a flexible schedule to meet deadlines. Qualifications - Must-Have: - PhD in Computational Biology, Bioinformatics, or Quantitative Biology; or - MS in Bioinformatics or Computational Biology with 3+ years applied research or industry experience; or - BS in Biology, CS, or Math with 5+ years applied quantitative biology or bioinformatics experience. - Working fluency in at least two of: - sequence analysis - phylogenetics - systems biology - statistical genetics - computational modeling - Comfortable reading and interpreting sequence alignments, phylogenetic trees, expression heatmaps, and pathway figures. - Clear technical writing; able to articulate reasoning step-by-step in written form. Requirements - Hourly contractor - Paid weekly Application Process - Upload resume - AI interview based on your resume - Submit form For details about the interview process and platform information, please check: Interview Process Details For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Role Description Analyze complex problems in physics, chemistry, mathematics, or biology to apply structured reasoning and improve AI model outputs. - Develop and implement quantitative methods and data analysis techniques to support interdisciplinary problem-solving. - Collaborate with AI research teams to ensure the accuracy and depth of AI-generated content. - Communicate solutions clearly and concisely to enhance understanding and application in scientific contexts. - Work independently and asynchronously to deliver high-quality outputs while meeting deadlines. Qualifications - Bachelor’s, Master’s, or PhD in a STEM field (or currently pursuing one). - 1+ year of relevant experience in academic, research, internships, or industry settings. - Strong problem-solving and analytical thinking skills. - Ability to work independently and deliver high-quality outputs. Company Description Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Support pharmacovigilance activities by authoring aggregate safety reports, preparing Risk Management Plans, conducting literature searches, and ensuring compliance with global regulatory requirements while maintaining high-quality standards.