We seek candidates for a Postdoctoral Research Position who will join the Ferretti lab at Virginia Tech to research sharks and other fish and their interaction with global fishing fleets. The postdoctoral associate will analyze and develop research on interactions between fish and fisheries by analyzing a diverse suite of large datasets from catch and effort data of regional fisheries management organizations (RFMO) to fisheries independent datasets such as scientific surveys and remote sensed tracking data from fishing vessels and tagged marine animals. The postdoctoral position will be based in the Ferretti lab (https://www.seaql.org/), at Virginia Tech’s main campus in Blacksburg, VA. The researcher will work with a multidisciplinary team using various approaches to integrate fisheries and ecological data into innovative analytical workflows supporting the management of fisheries and marine ecosystems.
We seek a creative individual with expertise in a relevant ecological, oceanographic, or fisheries discipline (e.g., quantitative marine ecology, conservation, fisheries science, statistical modeling –using both Bayesian and frequentist approaches – data science, machine learning and big data approaches, and spatial analyses) and the ability to effectively work in interdisciplinary teams and across scientific domains. The postdoctoral researcher will design and conduct analyses and models to quantify population reference points for fisheries management, habitat suitability models, population dynamics models, and large-scale analyses of industrial fishing fleets.
The researchers should have proficiency in programming languages such as R or Python, experience with state-of-the-art fisheries stock assessment models, approaches and software, data visualization, programming, data management/protocol, version control, coding, metadata, ability to manage servers and relational databases. We seek a person with experience and/or interest in both advancing scientific frontiers and addressing real-world challenges of sustainability in the ocean. The position is for one year, starting as soon as possible, with the potential for renewal pending funding availability.
The successful candidate will have a Ph.D. in a related field and preferably 1-2 years of experience in advanced technical work, including demonstrated ability to analyze complex systems and solve advanced technical problems, capability to source, handle and analyze large and disparate dataset types and formats, using spatial analytic methods, stock assessment models, Bayes and hierarchical modeling approaches, and experience in environmental data analysis/interpretation using statistical methods and/or modeling. Preference will be given to those with some proficiency in marine data science methods and big data approaches, strong quantitative skills, familiarity with issues related to fisheries and marine conservation, and demonstrated scientific productivity through peer-review publications. Candidates must possess strong teamwork skills and the ability to work effectively with students and staff, as well as within an interdisciplinary group of researchers. To be considered, interested candidates should provide a cover letter and Curriculum Vitae and the names and contacts of three references to Dr. Francesco Ferretti at email@example.com. Applications will be reviewed on a rolling basis.