Lead Laboratory Coordinator, Tree Ring Laboratory

The University of Arizona's Tree Ring Laboratory invites you to apply to the role of Lead Laboratory Coordinator (Laboratory Coordinator III).

Under the guidance of the Director, you will provide leadership and operational oversight for the Laboratory of Tree-Ring Research by coordinating laboratory activities and overseeing laboratory safety, inventory, and equipment. In this role, you will supervise and mentor students while welcoming and assisting visitors to the laboratory. You will also collaborate with faculty on research initiatives, contribute to the development and testing of innovative research methods, and support grant-related and outreach activities.

The Laboratory of Tree-Ring Research (LTRR) is a hub of interdisciplinary research, teaching, and outreach at the University of Arizona. Established in 1937, LTRR formalized the scientific study of tree rings in America and has since become a global leader in dendrochronology. Using the information preserved in the annual rings of trees, LTRR researchers work to better understand and quantify the complex interactions among Earth's climate, ecosystems, and societies. The laboratory is dedicated to developing and advancing novel approaches to address scientific questions of societal relevance while sharing these discoveries and their impacts with researchers, students populations, the general public, resource managers, and policymakers alike. If you are passionate about contributing to meaningful research and outreach in a collaborative and impactful environment, we invite you to join our team.

Outstanding U of A benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and qualified family members; retirement plans; access to U of A recreation and cultural activities; and more!

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In this role, you will:

• Lead the oversight of a dendrochronology laboratory in collaboration with the Director, including the mentoring, training, and supervising of students, staff, and visitors.
• Support the daily operations of the lab, including being the lead in charge of inventory control, safety compliance, and resource coordination.
• Support faculty research through the development, testing, and implementation of innovative analytical, computational, and image acquisition methodologies.
• Contribute to research advancement through assisting faculty in grant development and proposal writing while supporting laboratory curation, outreach, and educational initiatives that promote the dissemination and application of dendrochronological research.

Knowledge, Skills, and Abilities:

• Strong organizational skills, especially in assisting in managing operations, inventory, ordering, and maintenance.
• Excellent written and verbal communication skills.
• Ability to work both independently and collaboratively in a research environment.

Physical Requirements:

• Occasionally lifts/moves archival samples, boxes, and/or materials weighing up to 20 pounds.

This job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve.

• Bachelor's degree required.
• Minimum of 5 years of relevant work experience, or equivalent combination of education and work experience.
• Experience in a research laboratory or similar environment.

• Master's degree or PhD in Earth Science, Geosciences, Geography, Forestry, Environmental Science, or a related field (or equivalent combination of education and experience).
• Demonstrated experience in successfully supervising, training, and mentoring students, visiting researchers, and/or lab staff in laboratory methods, procedures, and safety.
• Experience and proficiency in R or Python.
• Previous experience with applications of computer vision, machine learning/AI, and/or high-resolution image acquisition.
• Previous hands-on experience in dendrochronology, including sample collection, preparation, and crossdating.