--- title: Remote researchers needed: Georgia Crop Phenology Research, Yield Loss Modeling, and Remote Sensing Validation for Apples, Tree Nuts, Stone Fruit, Berries, and Grapes at Responsible Innovations description: Scope of Work: Georgia Crop Phenology Research, Yield Loss Modeling, and Remote Sensing Validation for Apples, Tree Nuts, Stone Fruit, Berries, and Grapes About Responsible Innovations Responsible Inn --- # Remote researchers needed: Georgia Crop Phenology Research, Yield Loss Modeling, and Remote Sensing Validation for Apples, Tree Nuts, Stone Fruit, Berries, and Grapes **Company:** Responsible Innovations **Location:** Georgia **Posted:** 2026-08-11 **Apply by:** 2026-09-25 [Apply / View original posting](https://www.linkedin.com/jobs/view/4449824861) ## Job description Scope of Work: Georgia Crop Phenology Research, Yield Loss Modeling, and Remote Sensing Validation for Apples, Tree Nuts, Stone Fruit, Berries, and Grapes About Responsible Innovations Responsible Innovations (RI) began as a project focused on helping organizations navigate tradeoffs in food system change and adopt responsible, people-centered approaches. Over time, our work expanded into research, training, strategic advising, and the development of tools that support more equitable decision-making. Today, we operate as a global network of experts working across research institutions, development organizations, and the private sector. We specialize in social equity, gender integration, responsible innovation, and the co-creation of solutions with farmers and communities. Our team brings experience across Africa, Asia, Latin America, and North America, helping partners generate insights, strengthen capacity, and design programs that advance more sustainable and resilient food systems. Background Responsible Innovations (RI) is recruiting a multidisciplinary team of agricultural researchers and remote sensing specialists to support the implementation of a technical research project for a private sector client. The project will develop crop phenology, yield loss, and yield estimation workflows to support satellite-based crop monitoring and agricultural intelligence for specialty crops in Georgia. Target Crops The project will focus on the following crops: Apples, Almonds, Walnuts, Hazelnuts, Peaches, Nectarines, Blueberries, and Grapes Experts Sought RI is seeking a team of 3 to 5 experts with complementary expertise in one or more of the following areas: Pomology, Horticulture, Crop physiology, Phenology, Agronomy, Orchard systems, Agricultural modelling, Yield estimation, Remote sensing and Agricultural statistics Experts may contribute to one or more of the project workstreams based on their technical expertise. All work will be done remotely. Scope of Work Workstream 1: Apple Yield Loss Model Development Time commitment: ~150 hours The primary output of the task is a series of workflows that can be used to estimate yield reduction or yield risk in apples in a particular farm/ management block based on publicly available data sources (satellite imagery and climate data). Yield Reduction in this case is referring to a percentage decrease from a given field's theoretical yield potential that results from stress/ disease/ climatic events. The workflows should separate different categories of yield reduction (frost, heat stress, pest pressure…) and provide a series of instructions on how to estimate yield reduction as a percentage when certain variables meet certain criteria (for example: frost damage at a specific temperature, or stress equations and estimated yield loss based on satellite indices). If quantifiable relationships between variables and yield loss are not available (or have excessively low confidence), the team can quantify yield risk on a scale of 0.0 to 1.0 for a certain number of variables. The number of categories of yield reduction is up to the discretion of the team, but should aim to theoretically capture ~90% of the yield reduction variability. These workflows should be built in a way that outputs numerical estimates for yield reduction/ yield risk . Reviewers should only use academic literature or University Extension resources. Any use of A.I. should be rigorously cross-referenced and validated with information from reputable sources. Teams are encouraged to develop their own ideas and approaches but are welcome to reach out to and collaborate with the client. Outputs: Apple yield reduction workflows: Specific number of workflows depends on the categories identified for yield reduction and risk estimations. Workstream 2: Literature Review for Phenological Data Time commitment: ~150 hours The tasks below will be used to develop a yield reduction workflow for other crops of interest including: almonds, walnut, hazelnut, peaches/ nectarines, blueberries, and grapes . Researchers will identify and document available evidence on crop growth models, chilling and heat accumulation requirements, bloom requirements, yield impacts associated with insufficient chilling, frost damage thresholds, heat stress relationships, hail damage, and quantitative yield loss equations where available. Where robust equations do not exist, researchers should summarize the available evidence, identify knowledge gaps, and recommend appropriate approaches for estimating yield risk. All findings should be supported by peer-reviewed academic literature or University Extension resources and include appropriate citations. Workstream 3: Remote Sensing Consultation Time commitment: ~100-200 hours This would be a more flexible arrangement that would likely constitute a combination of: 1) Meetings and answers based on pre-submitted questions 2) Summary recommendations for the development of a validation plan. Including: a) Overall validation approaches for remote agronomic data b) Statistical approaches c) Calibration approaches d) Benchmarking approaches Ideally we would like to partner with a remote sensing specialist with a strong background in crop / agronomic applications. This would likely be a 4-6 month part-time contract of 8-12 hours a week, for a total of approximately 100-200 hours of contracted work total. Desired Qualifications for all workstreams Master's degree, PhD, or equivalent research experience in a relevant discipline. Demonstrated expertise in one or more of the target crops or technical areas. Experience conducting scientific literature reviews and synthesizing research findings. Strong technical writing and documentation skills. Experience with crop modeling, GIS, remote sensing, or agricultural statistics is an advantage. Familiarity with agricultural production systems in Georgia is highly desirable. Applications are welcome from individual consultants, university researchers, research institutes, and multidisciplinary teams. Application Requirements Interested candidates should submit the following to Rashmi Ekka at rashmi@responsibleinnovations.org : Curriculum Vitae (CV) highlighting relevant education, research experience, publications (if applicable), and expertise related to the target crops or technical disciplines. Statement of Interest (maximum two pages) describing: Relevant experience with one or more of the target crops or technical areas. Which workstream(s) the applicant is interested in contributing to. Their proposed approach to conducting the literature review, model development, or remote sensing validation activities. Previous experience developing crop models, phenological analyses, yield estimation methods, or remote sensing validation frameworks, where applicable. Examples of Relevant Work (optional but encouraged), such as publications, technical reports, datasets, or other work products demonstrating relevant expertise. Availability , including the anticipated start date and estimated weekly availability during the project period. Expected hourly rate Evaluation Criteria Applications will be evaluated based on: Technical expertise relevant to the target crops or workstreams. Demonstrated research and scientific writing experience. Experience translating scientific literature into practical models, workflows, or decision-support tools. Expertise in remote sensing, agricultural statistics, or crop modeling (where applicable). Ability to collaborate effectively within a multidisciplinary team. --- đŸ”” [Monitor similar jobs on Gurify](https://gurify.com/?utm_source=techgeo&utm_medium=jobboard&utm_campaign=monitor_similar&role=Remote+researchers+needed%3A+Georgia+Crop+Phenology+Research%2C+Yield+Loss+Modeling%2C+and+Remote+Sensing+Validation+for+Apples%2C+Tree+Nuts%2C+Stone+Fruit%2C+Berries%2C+and+Grapes) — get alerted when matching roles are posted in Georgia. ```json {"@context":"https://schema.org/","@type":"JobPosting","title":"Remote researchers needed: Georgia Crop Phenology Research, Yield Loss Modeling, and Remote Sensing Validation for Apples, Tree Nuts, Stone Fruit, Berries, and Grapes","description":"

Scope of Work: Georgia Crop Phenology Research, Yield Loss Modeling, and Remote Sensing Validation for Apples, Tree Nuts, Stone Fruit, Berries, and Grapes About Responsible Innovations Responsible Innovations (RI) began as a project focused on helping organizations navigate tradeoffs in food system change and adopt responsible, people-centered approaches. Over time, our work expanded into research, training, strategic advising, and the development of tools that support more equitable decision-making. Today, we operate as a global network of experts working across research institutions, development organizations, and the private sector. We specialize in social equity, gender integration, responsible innovation, and the co-creation of solutions with farmers and communities. Our team brings experience across Africa, Asia, Latin America, and North America, helping partners generate insights, strengthen capacity, and design programs that advance more sustainable and resilient food systems. Background Responsible Innovations (RI) is recruiting a multidisciplinary team of agricultural researchers and remote sensing specialists to support the implementation of a technical research project for a private sector client. The project will develop crop phenology, yield loss, and yield estimation workflows to support satellite-based crop monitoring and agricultural intelligence for specialty crops in Georgia. Target Crops The project will focus on the following crops: Apples, Almonds, Walnuts, Hazelnuts, Peaches, Nectarines, Blueberries, and Grapes Experts Sought RI is seeking a team of 3 to 5 experts with complementary expertise in one or more of the following areas: Pomology, Horticulture, Crop physiology, Phenology, Agronomy, Orchard systems, Agricultural modelling, Yield estimation, Remote sensing and Agricultural statistics Experts may contribute to one or more of the project workstreams based on their technical expertise. All work will be done remotely. Scope of Work Workstream 1: Apple Yield Loss Model Development Time commitment: ~150 hours The primary output of the task is a series of workflows that can be used to estimate yield reduction or yield risk in apples in a particular farm/ management block based on publicly available data sources (satellite imagery and climate data). Yield Reduction in this case is referring to a percentage decrease from a given field's theoretical yield potential that results from stress/ disease/ climatic events. The workflows should separate different categories of yield reduction (frost, heat stress, pest pressure…) and provide a series of instructions on how to estimate yield reduction as a percentage when certain variables meet certain criteria (for example: frost damage at a specific temperature, or stress equations and estimated yield loss based on satellite indices). If quantifiable relationships between variables and yield loss are not available (or have excessively low confidence), the team can quantify yield risk on a scale of 0.0 to 1.0 for a certain number of variables. The number of categories of yield reduction is up to the discretion of the team, but should aim to theoretically capture ~90% of the yield reduction variability. These workflows should be built in a way that outputs numerical estimates for yield reduction/ yield risk . Reviewers should only use academic literature or University Extension resources. Any use of A.I. should be rigorously cross-referenced and validated with information from reputable sources. Teams are encouraged to develop their own ideas and approaches but are welcome to reach out to and collaborate with the client. Outputs: Apple yield reduction workflows: Specific number of workflows depends on the categories identified for yield reduction and risk estimations. Workstream 2: Literature Review for Phenological Data Time commitment: ~150 hours The tasks below will be used to develop a yield reduction workflow for other crops of interest including: almonds, walnut, hazelnut, peaches/ nectarines, blueberries, and grapes . Researchers will identify and document available evidence on crop growth models, chilling and heat accumulation requirements, bloom requirements, yield impacts associated with insufficient chilling, frost damage thresholds, heat stress relationships, hail damage, and quantitative yield loss equations where available. Where robust equations do not exist, researchers should summarize the available evidence, identify knowledge gaps, and recommend appropriate approaches for estimating yield risk. All findings should be supported by peer-reviewed academic literature or University Extension resources and include appropriate citations. Workstream 3: Remote Sensing Consultation Time commitment: ~100-200 hours This would be a more flexible arrangement that would likely constitute a combination of: 1) Meetings and answers based on pre-submitted questions 2) Summary recommendations for the development of a validation plan. Including: a) Overall validation approaches for remote agronomic data b) Statistical approaches c) Calibration approaches d) Benchmarking approaches Ideally we would like to partner with a remote sensing specialist with a strong background in crop / agronomic applications. This would likely be a 4-6 month part-time contract of 8-12 hours a week, for a total of approximately 100-200 hours of contracted work total. Desired Qualifications for all workstreams Master's degree, PhD, or equivalent research experience in a relevant discipline. Demonstrated expertise in one or more of the target crops or technical areas. Experience conducting scientific literature reviews and synthesizing research findings. Strong technical writing and documentation skills. Experience with crop modeling, GIS, remote sensing, or agricultural statistics is an advantage. Familiarity with agricultural production systems in Georgia is highly desirable. Applications are welcome from individual consultants, university researchers, research institutes, and multidisciplinary teams. Application Requirements Interested candidates should submit the following to Rashmi Ekka at rashmi@responsibleinnovations.org : Curriculum Vitae (CV) highlighting relevant education, research experience, publications (if applicable), and expertise related to the target crops or technical disciplines. Statement of Interest (maximum two pages) describing: Relevant experience with one or more of the target crops or technical areas. Which workstream(s) the applicant is interested in contributing to. Their proposed approach to conducting the literature review, model development, or remote sensing validation activities. Previous experience developing crop models, phenological analyses, yield estimation methods, or remote sensing validation frameworks, where applicable. Examples of Relevant Work (optional but encouraged), such as publications, technical reports, datasets, or other work products demonstrating relevant expertise. Availability , including the anticipated start date and estimated weekly availability during the project period. Expected hourly rate Evaluation Criteria Applications will be evaluated based on: Technical expertise relevant to the target crops or workstreams. Demonstrated research and scientific writing experience. Experience translating scientific literature into practical models, workflows, or decision-support tools. Expertise in remote sensing, agricultural statistics, or crop modeling (where applicable). Ability to collaborate effectively within a multidisciplinary team.

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