Postdoctoral Scholar in Quantitative Marine Ecology

Dr. Alexa Fredston in the Department of Ocean Sciences at the University of California, Santa Cruz (UCSC) invites applications for the position of Postdoctoral Scholar in Quantitative Marine Ecology. The Fredston Lab uses large datasets, theoretical models, and a range of statistical tools to predict marine ecological responses to global change. The lab currently has two main themes: ecological forecasting (which focuses on modeling processes) and empirical biogeography (which focuses on explaining patterns).

The ecological forecasting theme includes the theoretical development and empirical application of process-based models, for predicting near-term range shifts in marine species and testing fundamental drivers of range dynamics. The empirical biogeography theme analyzes large-scale historical datasets to understand why species' ranges and range edges are where they are and how global change is reshaping populations, communities, and ecosystems. Some projects in the Fredston Lab connect these two themes, such as methodological improvements in how to conceptualize and quantify range edges. While Dr. Fredston's work has primarily used data on temperate fishes to date, she has broad interests in all marine taxa and systems.

This two-year postdoc position is funded by Dr. Fredston's startup funds at UCSC and thus represents a uniquely open-ended opportunity for the successful candidate to co-develop novel and independent research projects. The postdoc will also have opportunities to write grants, participate in working groups, join collaborations, engage with natural resource managers and conservation practitioners, and work with graduate and undergraduate students. The postdoc will have a primary research project that will be mutually agreed upon with Dr. Fredston. The Fredston Lab is a highly cooperative work environment, thus the ability to consistently demonstrate excellent communication skills; successfully collaborate with faculty, researchers, and students; and contribute to a supportive and inclusive professional culture are essential components of the position.

The ideal candidate for this position will leverage their quantitative skill set and ecological expertise to lead exciting and novel research in marine biogeography, population ecology, or community ecology. The ideal candidate will also demonstrate the following qualities:

• Have expertise in theoretical and/or quantitative biology or ecology, or a closely related field.
• Have experience with one or more modeling approaches commonly used in ecology, such as: population modeling, spatio-temporal modeling, individual-based modeling, integral projection modeling, species distribution modeling, Bayesian hierarchical modeling, dynamic occupancy modeling, structural equation modeling, empirical dynamic modeling, and/or network modeling.
• Have familiarity with some form(s) of data and observations available for monitoring marine biodiversity, e.g., trawl surveys, acoustic surveys, visual surveys, tagging data, mark-recapture data, and eDNA.
• Be proficient in at least one open-source programming language, such as R or python.
• Have experience using version control software and platforms such as Git and GitHub.
• Be committed to open science principles, such as code review and data sharing.
• Have taken advanced courses in modeling, statistics, and/or data analysis.
• Have experience leading independent research projects, and a record of first-author publications (commensurate with experience) in related topics.
• Be excited about doing highly quantitative work that is relevant to natural resource management and biodiversity conservation.

Candidates who possess some but not all of the above areas of expertise are still encouraged to apply.

The hiring unit will not sponsor employment-eligible immigration statuses for this position.

Fredston Lab: https://www.alexafredston.com/

Ocean Sciences Department: https://science.ucsc.edu/department/ocea/

• A PhD (or equivalent foreign degree) in earth, environmental, biological, chemical, physical, or social sciences; engineering; mathematics, statistics, or a related discipline. Ph.D. must be in hand at the time of the appointment (rather than at the time of application).
• Demonstrated experience with computational modeling and data analysis methods.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.

• "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment, discrimination, dishonesty, or unethical conduct, as defined by the employer.
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The University of California is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories covered by the UC Anti-Discrimination Policy.

It is the policy of the University of California to undertake affirmative action and anti-discrimination efforts, consistent with its obligations as a Federal and State contractor.

If you need accommodation due to a disability, please contact Disability Management Services at roberts@ucsc.edu (831) 459-4602.

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The University of California offers a competitive benefits package and a number of programs to support employee work/life balance.

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