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Full Time Ecological Modeling Jobs (NOW HIRING)

Energy Engineer II

Wilmington, DE · On-site

$75K - $100K/yr

Job Type Full-time Description Job Type: Full-time, Exempt Location: Wilmington, DE Hiring Rate ... Position Overview: New Ecology, Inc. is seeking an engineering candidate with 3-5 years of ...

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Full Time Ecological Modeling information

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How much do full time ecological modeling jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for full time ecological modeling in the United States is $40.33, according to ZipRecruiter salary data. Most workers in this role earn between $31.25 and $43.51 per hour, depending on experience, location, and employer.

What is full time ecological modeling?

Full time ecological modeling involves using mathematical, statistical, and computational tools to simulate and understand ecological systems and processes. Professionals in this field develop and apply models to study topics like population dynamics, species interactions, ecosystem functions, and the impacts of environmental changes. These models help guide conservation efforts, resource management, and environmental policy decisions. The work typically requires strong analytical skills and knowledge of ecology, mathematics, and programming.

What are the key skills and qualifications needed to thrive as a full time ecological modeler?

A Full Time Ecological Modeler typically requires a strong background in ecology, mathematics, and statistics, along with at least a bachelor's or master's degree in ecology, environmental science, or a related field. Proficiency in modeling software such as R, Python, MATLAB, and GIS tools, as well as experience with statistical and simulation modeling techniques, is essential. Strong analytical thinking, attention to detail, and effective communication skills help translate complex ecological data into actionable insights for diverse stakeholders. These competencies are crucial for developing reliable ecological models that inform environmental management, policy decisions, and conservation strategies.

What are some typical collaborative projects or interdisciplinary teams that a full time ecological modeler works with?

Full Time Ecological Modelers frequently collaborate with ecologists, data scientists, GIS specialists, and sometimes policy experts or resource managers. These interdisciplinary teams work together to design studies, collect and analyze ecological data, and develop predictive models to inform conservation or management decisions. Effective communication and teamwork are essential, as modelers often need to translate complex modeling results into actionable insights for non-technical stakeholders. This collaboration enhances both the scientific rigor and real-world impact of ecological modeling projects.

What is the difference between Full Time Ecological Modeling vs Full Time Environmental Data Analysis?

AspectFull Time Ecological ModelingFull Time Environmental Data Analysis
Required CredentialsDegree in Ecology, Environmental Science, or related field; experience with modeling softwareDegree in Data Science, Statistics, or Environmental Science; proficiency in data analysis tools
Work EnvironmentResearch labs, environmental agencies, consulting firmsResearch institutions, government agencies, consulting firms
Industry UsageDesigns ecological models to predict environmental impactsAnalyzes environmental data to inform decisions and policies

While both roles involve environmental data, Full Time Ecological Modeling focuses on creating models to simulate ecological systems, whereas Full Time Environmental Data Analysis emphasizes interpreting environmental data sets to support decision-making.

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What other helpful pages are available for Full Time Ecological Modeling?

Other pages related to Full Time Ecological Modeling:

Infographic showing various Full Time Ecological Modeling job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 80% Physical, 4% Hybrid, and 16% Remote job distribution, with an average salary of $83,896 per year, or $40.3 per hour.

Tenure Track: Assistant Professor - Artificial Intelligence in Soil and Crop Sciences

College Station, TX • On-site

Texas A&M University
Colleges, Universities, and Professional Schools • 1 - 5K employees

Full-time

Posted 20 days ago


Key responsibilities

  • Develop a highly impactful, extramurally funded research program integrating artificial intelligence into soil and crop sciences.

  • Develop and teach two courses in the Department of Soil and Crop Sciences, including an introductory course on artificial intelligence in agriculture and a stacked undergraduate/graduate course on precision agriculture.

  • Advise and mentor undergraduate and graduate students, postdoctoral scientists, and research technicians, and participate in outreach and service activities.


Texas A&M University rating

7.8

Company rating: 7.8 out of 10

Based on 146 frontline employees who took The Breakroom Quiz


Job description

Position Description: The Department of Soil and Crop Sciences in the College of Agriculture and Life Sciences at Texas A&M University in College Station, TX, seeks outstanding applicants for a tenure-track Assistant Professor faculty position in Artificial Intelligence in Soil and Crop Sciences . This is a 9-month, full-time, tenure-track faculty position with research, teaching, outreach, and service responsibilities. This position is part of a four-position cluster hire in AI in Agriculture across the College of Agriculture and Life Sciences to develop an undergraduate minor in AI-Enabled Agricultural Systems and build research capacity in this area. The anticipated start date is August 16, 2027.
Major Duties and Responsibilities : The successful applicant will be responsible for developing a highly impactful, extramurally funded research program integrating artificial intelligence into soil and crop sciences. Their work would use artificial intelligence to improve knowledge and outcomes by leveraging and integrating varied relevant data (which may include agronomic, environmental, economic, genomic, nutrition, pest and disease, phenotypic, physiological, management, microbiome, soil, weather, and water), as well as applications and technologies (which may include precision soil and water management, decision-support tools, precision human nutrition, remote sensing, robotics, sensors and variable-rate applications). The successful applicant must demonstrate strong expertise in artificial intelligence, machine learning, data analytics, or related computational approaches, along with experience in applying these tools to soil, crop, environmental, or biological systems.
The individual will work closely with agronomists, computer scientists, crop physiologists, data scientists, engineers, genomics and genetics researchers, plant breeders, soil scientists and water researchers in Texas A&M AgriLife Research and the Texas A&M AgriLife Extension Service, both on and off-campus. Interdisciplinary collaborations with scientists and stakeholders in the region, nationally, and internationally is expected.
The individual will develop and teach two courses in the Department of Soil and Crop Sciences. One course is expected to be an introductory undergraduate course on artificial intelligence and its applications in agriculture and environmental sciences. Emphasis will be given to Large Language Models and their integration into chatbots and virtual consultants. The second course is expected to be a stacked undergraduate/graduate course with a focus on precision agriculture. One or both of these courses should include topics such as agentic AI for autonomous crop and pest management decision-making, foundation and multimodal models, human-robot collaboration for field operations, causal machine learning for interpretable agronomic and ecological modeling, digital twins for real-time crop system simulation and scenario planning, and reinforcement learning for management of cropping systems; or similar topics as they emerge. The individual will be expected to provide substantial leadership in developing a new certificate program in digital agriculture and AI applications in soil and crop sciences.
The individual will advise and mentor undergraduate and graduate students, postdoctoral scientists, and research technicians. They, along with their mentees, will be expected to publish regularly in peer-reviewed journals appropriate to the discipline. They will participate in outreach and service activities related to the position.
Distribution of Effort: 60% research, 30% teaching, and 10% outreach and service
Qualifications
Required Qualifications: Ph.D. or equivalent doctoral degree in environmental science, plant or crop science, agronomy, soil science, computer science, bioinformatics, mathematics, statistics, remote sensing, agriculture, biosystems engineering, electrical engineering, or related disciplines. Candidates who have completed all Ph.D. requirements except the dissertation (ABD) will be considered provided they demonstrate clear progress toward completion prior to the position start date. Strong knowledge and experience in both artificial intelligence as well as agricultural, soil or environmental data are required.
Desired Qualifications: Experience working with crops, field-based research, handling large datasets, interdisciplinary collaboration, sensing technologies and grant writing is desired. Additional qualifications include excellent oral and written communication skills, a good track record of publishing in peer-review journals, and teaching experience.
Salary will be commensurable with qualifications and experience.
Application Instructions
Applications will only be accepted online at https://apply.interfolio.com/189790 . Applicants must upload a cover letter (2 pages), curriculum vitae, a list of three referees and their contact information; and a personal statement of their plans for research, teaching, and service (3 pages total). Please clearly indicate in the research and teaching sections a vision for how AI will impact the practice of science and teaching and learning. To be given full consideration, please submit applications by November 18, 2026. The position will remain open until a suitable candidate is identified. The anticipated start date is August 16, 2027.
For fruther information, please contact the Search Committee Chair, Dr. Seth Murray at seth.murray@ag.tamu.edu
Application Process
This institution is using Interfolio's Faculty Search to conduct this search. Applicants to this position receive a free Dossier account and can send all application materials, including confidential letters of recommendation, free of charge.
Apply Now

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