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Computational Ecology Jobs (NOW HIRING)

Oxman

Computational Ecologist

New York, NY · On-site

$152K - $241K/yr

Working across disciplines-from architecture and ecology to materials science and computation, we ... D. or equivalent experience in Computer Science, Computational Ecology, Systems Biology, or a ...

Oxman

Computational Designer

New York, NY · On-site

$75K - $225K/yr

Working across disciplines-from architecture and ecology to materials science and computation-we ... Role Overview OXMAN is seeking a Computational Designer to join the EDEN design team and develop ...

Tuskegee University

We prefer candidates whose research uses modern datasets and computational approaches, including ... D. in Ecology and Evolution Biology, Environmental Science, Marine Science or a closely related ...

Oxman

Machine Learning Research Engineer

New York, NY · On-site

$142K - $224K/yr

Collaborate with computational ecologists and data scientists to integrate generative design with ecosystem simulation models. * Align design outputs with ecological performance indicators such as ...

Louisiana State University

Potential areas of research are broad and include evolutionary biology of plant-pathogen interactions, epidemiology, ecology, statistical modeling, computational biology, genomics, structural biology ...

Louisiana Workforce Commission

Potential areas of research are broad and include evolutionary biology of plant-pathogen interactions, epidemiology, ecology, statistical modeling, computational biology, genomics, structural biology ...

LSU AgCenter

Potential areas of research are broad and include evolutionary biology of plant-pathogen interactions, epidemiology, ecology, statistical modeling, computational biology, genomics, structural biology ...

Auburn University

TES Research Associate

Auburn, AL · On-site

The role involves developing computational models and integrating multi-source datasets to advance understanding in ecological traits and plant physiological processes. Responsibilities : • ...

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Computational Ecology information

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How much do computational ecology jobs pay per hour?

As of Jun 10, 2026, the average hourly pay for computational ecology in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

What is computational ecology?

Computational ecology is a scientific field that uses mathematical models, computer simulations, and data analysis to study ecological systems and processes. By integrating computers and algorithms with ecological theory, computational ecologists can analyze complex interactions within ecosystems, predict environmental changes, and interpret large datasets from field observations or remote sensing. This approach helps researchers make informed decisions about biodiversity conservation, ecosystem management, and understanding the impacts of human activities on natural habitats.

What are the key skills and qualifications needed to thrive as a Computational Ecologist, and why are they important?

To thrive as a Computational Ecologist, you need a strong background in ecology, statistics, and quantitative modeling, typically supported by an advanced degree in ecology, biology, or a related field. Proficiency with programming languages such as R or Python, experience with GIS software, and familiarity with data analysis tools are essential. Strong analytical thinking, problem-solving abilities, and effective communication skills help in translating complex data into actionable ecological insights. These skills are crucial for addressing environmental challenges, developing models, and supporting evidence-based conservation decisions.

What are some common challenges faced by computational ecologists when integrating field data with complex ecological models?

Computational ecologists often encounter challenges related to the quality, scale, and completeness of field data when integrating it with complex models. Field data may be sparse, collected at different spatial or temporal resolutions, or subject to observational errors, which can complicate model calibration and validation. Additionally, aligning diverse datasets and ensuring computational models accurately represent ecological processes require strong collaboration between field researchers and computational teams. Overcoming these challenges typically involves data cleaning, statistical analysis, and iterative model refinement, making cross-disciplinary communication and problem-solving essential skills in this role.

What is the difference between Computational Ecology vs Ecologist?

AspectComputational EcologyEcologist
Required CredentialsMaster's or Ph.D. in Ecology, Environmental Science, or related fields; strong programming skillsBachelor's or higher in Ecology, Biology, Environmental Science; fieldwork experience
Work EnvironmentResearch labs, data analysis centers, computational environmentsField sites, laboratories, research institutions
Industry UsageAcademic research, environmental consulting, government agenciesConservation organizations, research institutions, government agencies

Computational Ecology focuses on using computer models, simulations, and data analysis to study ecological systems, often requiring programming skills. Ecologists typically conduct fieldwork and laboratory research to observe and analyze ecosystems directly. While both roles aim to understand ecological processes, Computational Ecology emphasizes data-driven modeling, whereas Ecologists focus on empirical observation and field studies.

More about Computational Ecology jobs
What states have the most Computational Ecology jobs? States with the most job openings for Computational Ecology jobs include:
What job categories do people searching Computational Ecology jobs look for? The top searched job categories for Computational Ecology jobs are:
Computational Ecology jobs near you
Computational Ecologist

Computational Ecologist

Oxman

New York, NY • On-site

$152K - $241K/yr

Full-time

Posted 17 days ago

Job description

OXMAN
OXMAN is a nature-based research and design company based in Manhattan. We incubate ventures and technologies that reimagine the relationship between humanity and the natural world. Working across disciplines-from architecture and ecology to materials science and computation, we develop nature-centric solutions to critical environmental challenges.
EDEN
Nature provides humanity with services that are critical for survival: the sequestration of carbon, the filtration of water, and the production of the air we breathe. EDEN works to strengthen and regenerate these natural processes by cultivating biodiverse, resilient ecosystems that sustain life for all species-human and non-human alike.
EDEN is a digital design environment for engineering and designing ecosystems, modeling the flows, relationships, and processes that sustain them. We build tools that quantify how landscapes can be engineered to achieve specific performance goals, cooling cities, filtering water, sequestering carbon, and protecting key species, and use them to guide the design of ecologically active sites.
One hectare of well-designed landscape can sequester up to four times the annual emissions of an average home, filter enough water to support thirteen neighborhoods, and reduce ambient temperatures by more than ten degrees. EDEN enables designers to plan intentionally for these outcomes through analysis, simulation, and optimization, turning ecological function into an actionable design parameter.
Our design team works directly with clients to apply these tools toward site-specific goals, from logistics campuses and residential communities to rewilding and climate-resilient developments. Together with our clients, we are designing biodiverse, productive environments that serve both humanity and nature.
Key Responsibilities
  • Conceptualization and Research: Research and identify key ecosystem behaviours and interactions to create a comprehensive conceptual framework for general ecosystem modelling
  • Ecosystem Behaviour Modelling: Leading of the modelling of core ecosystem dynamics and interactions as defined in the conceptualization phase such as plant growth and succession etc.
  • Ecosystem Metrics Development: Development of quantitative metrics to assess ecosystem health, stability, and service provision.
  • Implementation and Documentation: Models will be implemented in a computationally efficient framework with thorough documentation to ensure usability and reproducibility.
  • Help in the gathering and integration of relevant environmental, ecological, and spatial data to underpin model parameters and validate model outcomes.
  • Conduct data analysis to in order to derive key insights necessary to develop ecosystem models and validate model parameters.
  • Technical documentation: Prepare comprehensive documentation outlining model assumptions, data sources, code structure, and operation for using and maintaining the models.
  • Continually communicate with the OXMAN team to ensure review of research, implementation, and seamless integration of the model into their workflows.
  • Participate in regular progress meetings (weekly or biweekly) with the team to review milestones, discuss challenges, and plan next steps.
  • Provide status updates summarizing progress, challenges encountered, and any adjustments to the project plan.
Key Goals and Outcomes
  • Development, deployment, and validation of a general ecosystem model within two quarters of the start date
Required Experience
  • A Ph.D. or equivalent experience in Computer Science, Computational Ecology, Systems Biology, or a related field.
  • Strong programming skills in languages such as Python, C++, or similar, with experience in frameworks like PyTorch, or JAX.
  • Strong foundation in modeling techniques (e.g., differential equations, agent-based modeling, network models, Bayesian approaches) for simulating ecological processes or population dynamics.
  • Experience handling large and often messy datasets common in ecology (e.g., climate data, remote sensing imagery, biodiversity records). Knowledge of spatial databases, parallel computing, or cloud-based data storage is a plus
Technical Skills
  • Python (NumPy/SciPy/pandas), reproducible research workflows, and Git-based version control
  • High-performance model implementation (vectorization, profiling/optimization); familiarity with PyTorch or JAX
  • Ecological modeling methods: agent-based, ODE/PDE, network, and Bayesian/statistical modeling; uncertainty quantification
  • Geospatial analytics (GIS; GeoPandas/rasterio/GDAL) and spatial databases (e.g., PostGIS) for integrating environmental and biodiversity data
  • Remote sensing and gridded data handling (e.g., xarray; land cover/land use change; climate rasters); comfort with messy real-world datasets
  • Clear technical documentation (assumptions, data provenance, APIs) and maintainable code (testing, modular design)
Essential Qualities
  • Systems-level thinker who can translate ecological theory into tractable computational abstractions
  • Strong research judgment: literature synthesis, hypothesis framing, and disciplined model validation
  • Pragmatic engineer: prioritizes computational efficiency, robustness, and reproducibility over "toy" prototypes
  • Comfortable working with uncertainty, noisy data, and incomplete ground truth, typical of ecological problems
  • Clear communicator in interdisciplinary teams (design, biology, engineering); proactive stakeholder management
  • High ownership: independently drives milestones while aligning work to EDEN workflow integration needs

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