[R-jobs] Computational Ecologist Job at NOAA in Silver Spring, MD -- Marine Wildlife Spatial Modeling in R

Ramesha Karunakaran k@r@me@h@ @end|ng |rom gm@||@com
Tue Apr 9 06:34:41 CEST 2013


PFA resume for the below position.


On Tue, Apr 9, 2013 at 12:51 AM, Brian Kinlan (NOAA Affiliate) <
brian.kinlan using noaa.gov> wrote:

> The NOAA National Centers for Coastal Ocean Science is hiring a
> Computational Ecologist, a statistical/computational ecologist with
> experience fitting advanced spatial models to marine wildlife survey data
> (e.g., seabirds and marine mammal transects, fisheries trawl surveys) in R
> and other statistical languages. This is a full-time, long-term stable
> contract position. We are looking for an expert R programmer with
> experience in spatial modeling, especially of marine wildlife survey
> transect data (e.g. seabirds, marine mammals). Please note that this is a
> contract position, so rather than applying directly to NOAA the link below
> directs you to the contracting company (CSS-Dynamac, Inc.). We are looking
> to hire someone immediately.
> ----------------
> Computational Ecologist
> Contract position with NOAA's National Ocean Service, National Centers for
> Coastal Ocean Science, Biogeography Branch (Contract Company:
> http://www.css-dynamac.com/)
> Apply for this job online at https://jobs-**consolidatedsafety.icims.com/*
> *jobs/1486/job <https://jobs-consolidatedsafety.icims.com/jobs/1486/job>
> Responsibilities:
> A person with experience or academic training in quantitative ecology,
> advanced statistical modeling, computational analysis, and scientific
> programming in R and Matlab; who also has demonstrated interest and
> experience in advanced spatial analysis, is being sought for a full-time
> contract position with the National Oceanic and Atmospheric
> Administration’s (NOAA) National Centers for Coastal Ocean Science (NCCOS).
> NCCOS’ Biogeography Branch conducts ecological and oceanographic studies to
> map, characterize, assess, and model the spatial distributions and
> movements of marine organisms across habitats throughout the United States
> and Island Territories. We are seeking an individual with a broad suite of
> quantitative, statistical, and computational skills. A strong background in
> statistical modeling of spatial ecological data with some experience in
> marine sciences is preferred. The successful candidate will join an
> experienced scientific team at the forefront of marine ecological
> predictive analytics. The initial assignment for this position will involve
> developing, implementing, and running machine-learning models for
> predictive spatio-temporal modeling of marine bird and groundfish
> distributions to support marine planning processes. Additional potential
> projects include predictive modeling of deep sea corals, marine mammals,
> sea turtles, marine fish, fishing fleets, and marine ecosystem processes. 
> Core responsibilities
> Provide statistical, computational, and analytical support to projects
> that use predictive statistical models, in conjunction with large wildlife
> survey and oceanographic databases, to provide spatially-explicit maps and
> analyses that answer questions of marine management and conservation
> relevance.
> Design and implement spatial and spatio-temporal statistical models of
> marine species’ distributions (e.g., seabird and marine mammal occurrence
> probability and abundance), marine habitat, and marine ecosystem properties
> Develop and maintain computer code to interface with large oceanographic
> and ecological databases and mine these databases to improve predictive
> models
> Assess model performance and uncertainty in management-relevant scenarios
> Assist with writing journal articles/reports and present at scientific
> conferences
> Offer technical guidance for selection and implementation of different
> statistical methods to detect patterns in wildlife surveys.
> Explain statistical results as they relate to project goals and summarize
> results in the form of tables, figures, journal articles and technical
> reports.
> Travel to federal and state laboratories and academic institutions as part
> of collaborative research projects
> Develop, maintain, and grow a codebase for advanced spatial analysis
> Apply new developments in statistical modeling to a marine
> ecological/wildlife survey context
> Implement model selection, assessment, and validation algorithms
> Develop, maintain, and grow oceanographic and ecological geo-databases
> Build a database of oceanographic and environmental predictor variables of
> relevance to marine ecological modeling
> Analyze satellite and observational datasets and raw ocean model outputs
> to develop derived products that improve predictive models
> Automate data acquisition, data mining, model assessment & QA/QC processes
> Qualifications:
> Essential
> Advanced degree (Masters or PhD), or equivalent experience, in
> Quantitative Ecology, Applied Statistics, or similarly highly quantitative
> field. Ecology, Marine Science and related advanced degrees also acceptable
> with demonstrated evidence of a strong quantitative focus and statistical
> and computer programming expertise described below
> Must be proficient and highly experienced with R and Matlab (3-5+ years
> experience with one or both of these languages); a code sample may be
> requested to demonstrate proficiency
> Experience implementing a variety of spatially-explicit statistical models
> in R and/or Matlab, including at least 3 of the following: machine learning
> models (e.g., component-wise boosting), geostatistical models, GLMMs, GAMs,
> regression trees/forests
> Ability to independently identify, analyze and solve complex statistical
> and computational problems
> Demonstrated written and oral scientific communication skills
> Able to work effectively in a dynamic, fast-paced, team-oriented
> multi-project environment
> Preferred
> Experience with spatial analysis of wildlife survey data, especially
> marine bird data, in the marine environment
> Knowledge of ecology, marine science, oceanography, and/or a related field
> Ability to interface with large databases through THREDDS/ERDDAP servers
> in R and/or Matlab
> Experience working with ocean remote sensing data, numerical ocean model
> outputs (e.g., ROMS), and large distributed oceanographic databases
> Proficiency with programmable GIS (e.g., Python scripting with ArcGIS or
> equivalent); Experience with geostatistics (gstat, ESRI Geostatistical
> Analyst, rgeos, GSLIB, or equivalent)
> Although not required, we value experience developing hierarchical
> Bayesian or Approximate Bayesian models on large spatial datasets
> Record of academic publication
> Apply for this job online at https://jobs-**consolidatedsafety.icims.com/*
> *jobs/1486/job <https://jobs-consolidatedsafety.icims.com/jobs/1486/job>
> To discuss the position or for more information contact:
> Dr. Brian Kinlan
> Marine Spatial Ecologist
> NOAA NOS National Centers for Coastal Ocean Science
> Brian.Kinlan using NOAA.gov
> --
> *********************************************
> Brian P. Kinlan, Ph.D
> Marine Spatial Ecologist
> NOAA National Ocean Service
> Contractor, CSS Inc.
> NCCOS-CCMA-Biogeography Branch
> 1305 East-West Hwy, SSMC-4, N/SCI-1, #9224
> Silver Spring, MD 20910-3278
> http://ccma.nos.noaa.gov/**about/biogeography/<http://ccma.nos.noaa.gov/about/biogeography/>
> *********************************************
> Disclaimer: Any views or opinions expressed in this message are those of
> the sender, not NOAA, the United States Government or its agents, or
> Consolidated Safety Services, Inc.
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