Apply at bit.ly/HabitatABM
Review Date (IRD):* 09-24-2020*
The Institute of Marine Sciences [https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fims.ucsc.edu%2F&data=02%7C01%7Cpat.anderson%40uconn.edu%7C877d5ddd2e2e42a85ea808d859585c45%7C17f1a87e2a254eaab9df9d439034b080%7C0%7C0%7C637357583351646007&sdata=d7YlnjkaA3DZlDeGhKOjsz1UgrUIpdL1FUYHQVanNl8%3D&reserved=0] at the University
of California, Santa Cruz (UCSC), working in conjunction with the NOAA
National Marine Fisheries Service Southwest Fisheries Science Center (NOAA
Fisheries), invites applications for the position of Staff Research
Associate, under the direction of Dr. Peter Dudley, the staff research
associate will join a team developing a model to assess the effect of
habitat alterations on anadromous fish on large rivers. Humans have and
continue to alter many large rivers both for human and wildlife needs.
Agencies need to assess how these human actions affect the resident fish if
managers are to mitigate the effects of human actions, recover populations
of threatened fish species, and effectively manage native fish populations.
We are developing a modeling tool which will allow agencies to predict the
effect of proposed habitat altering actions on native anadromous fish
populations. This modeling tool will be spatially explicit and use an
individual based modeling framework. The staff research associate will aid
in model development by mining scientific literature and reports for data,
aggregating and synthesizing the data necessary for model development,
maintaining a database, conducting basic statistical analysis especially
regressions, and performing basic geographic information analysis as
necessary. These tasks require the ability to critically analyze scientific
literature and extract data from it based on understanding of experimental
methods, statistical analysis, and scientific modeling needs. If the data
found is of sufficient quality, the staff research associate will have the
opportunity to assist in the publication of a meta-analysis peer reviewed
article. This is an exciting opportunity to both conduct fundamental
scientific research into the effects of habitat alteration of resident fish
and help in developing a tool which government agencies will use to assess
the effects of their habitat alterations on resident fish populations.
While the goal is to have a model that will be general enough to operate on
many rivers, the initial use will be on rivers in the Sacramento Basin,
California.
Applicants with expertise in any of the following areas are strongly
encouraged to apply:
Experience searching literature using web portals such as Web of Science
and Google Scholar
Experience critically synthesizing scientific literature and inputting
information into spreadsheets or databases
Experience using scientific models
Experience with basic statistical techniques or knowledge of R (statistical
programing language)
*Salary Information*: $58,727.18/year. Salary commensurate with skills,
qualifications and experience.
Required Qualifications
Knowledge such as attained in upper division coursework leading to a
Bachelor Degree in Biology, Fisheries, Fisheries Science, Wildlife,
Zoology, or other related field or combination of education and work
experience.
Strong written and verbal communication and interpersonal skills.
Good organizational, time management and problem-solving skills.
Ability to exercise flexibility, initiative, good judgment and discretion.
Ability to work well independently and as part of a team.
Computer skills or knowledge should include Word, Excel, Power Point, and
Access.
Ability to conduct comprehensive literature searches using web portals such
as Web of Science and Google Scholar.
Preferred Qualifications
Knowledge such as attained in upper division coursework leading to a Master
Degree in Biology, Fisheries, Fisheries Science, Wildlife, Zoology, or
other related field or combination of education and work experience.
Experience using GIS software.
Experience with R (statistical programing language).
Experience using scientific models.