R sig jobs - Apr 2013 - Computational Ecologist Job at NOAA in Silver Spring, MD -- Marine Wildlife Spatial Modeling in R

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
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
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 at 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.

Hi,

PFA resume for the below position.

Thanks,
K.Ramesha


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