
Please feel free to forward to job ad to all relevant departmental 
listservs and job boards!
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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
*
*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*

 1. 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
 2. 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
 3. 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

*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@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/
*******************************************

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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