Organisation/Company: Université de Strasbourg
Researcher Profile: First Stage Researcher (R1) Recognised Researcher (R2)
Best Consideration Date: 01/15/2022
Job Status: Full-time
Hours Per Week: 36
Salary: Commensurate with experience
Open Position in Remote Sensing and Machine Learning Applications for Agriculture and Food Security at Postdoc/Research Scientist Level
The University of Strasbourg, ICube is seeking an outstanding researcher at the Post-doctoral/Research Scientist level, with a strong interest in agriculture and machine learning to join a diverse team working on satellite remote sensing applications for agricultural monitoring and food security, within the framework of the ESA World Cereal Project and the NASA Harvest Program. World Cereal, led by VITO, is an innovative and ambitious ESA activity that is developing an open system for generating accurate, global and seasonally updated cropland extent, crop type and irrigation maps. NASA Harvest is NASA's Food Security and Agriculture program, focused on advancing the use of earth observations applications for food security, stable agricultural markets and sustainability. The successful candidate will work on research related to remote sensing applications to agricultural monitoring in the context of food security and climate change. This position will support work related to the development, implementation and scaling of cropland and type mapping, ground data collection, crop yield forecasting, and cropping practices in order to inform key agricultural and food security decisions by a range of public and private stakeholders. This research will be carried out through the use of a wide range of satellite data, unique ground collected data-sets, global archives of diverse socioeconomic data and statistics.
The successful applicant should hold PhD in computer science, remote sensing, agricultural sciences, climatology, physics, engineering, mathematics, or related fields. A strong programming background (especially Python, R, IDL, or C++), and an interest in agriculture and food security research and applications is required. Experience with working with Google Earth Engine, Github, and machine learning libraries (i.e. TensorFlow, Keras, PyTorch) are a plus. The candidate will be expected to work well and collaboratively within a diverse team and distributed team.
We invite applications from individuals with a passion for applying scientific, geospatial, and creative thinking to address global issues. We value each member of our team and seek to provide professional and intellectual development opportunities to the selected candidate.
Applications should include:
- A personal statement of background and experience relevant to the position,
- A signed and dated Curriculum Vitae
- The names and email addresses of 2-3 references.
University of Strasbourg is an equal opportunity employer.
For best consideration, please apply by January 15th 2021, though the position will remain open until filled. Please send applications to firstname.lastname@example.org cc to email@example.com.
Location: GREENBELT, MD, United States
Date Posted: Oct 2, 2021
Category: Engineering and Sciences
Subcategory: Research Scientist
Shift: Day Job
Travel: Yes, 10 % of the Time
Minimum Clearance Required: None
Clearance Level Must Be Able to Obtain: Public Trust
Potential for Remote Work: No
Benefits: Click here
SAIC seeks to hire a Scientific Programmer Analyst to support the Hydrological Sciences Laboratory (HSL) at NASA Goddard Space Flight Center in Greenbelt, MD. Successful candidate will participate/lead in the design and implementation of a soil moisture-based agricultural yield forecasting system. Key responsibilities include the management of remote sensing, modeled and reference datasets, system design and functional testing of the software. The candidate should have experience with remote sensing datasets, structured programming, computing platforms and environments and experience/interests in land surface modeling, visible/near infrared, and microwave remote sensing, agricultural mapping/forecasting, statistics, and/or land data assimilation. A good knowledge of earth science data formats is expected and experience in working with satellite datasets is needed. The candidate must also be knowledgeable in visualization/analysis packages and software such as python, GrADS, NCL, IDL, Matlab and GIS. It is desirable that the incumbent has a MS/PhD in computer science, geophysics, hydrology, or related disciplines. The individual should have good communication (written and oral) skills. Experience in project coordination and writing and reviewing technical reports is also expected.
TYPICAL EDUCATION AND EXPERIENCE:
MS/PhD in computer science, geophysics, hydrology, or related disciplines.
The candidate should have experience with remote sensing datasets, structured programming, computing platforms and environments and experience/interests in land surface modeling, microwave remote sensing and/or land data assimilation. A good knowledge of earth science data formats is expected and experience in working with satellite datasets is needed. The candidate must also be knowledgeable in visualization/analysis packages and software such as python, GrADS, NCL, IDL, Matlab and GIS. The individual should have good communication (written and oral) skills. Experience in project coordination and writing and reviewing technical reports is also expected.
View additional details and the original posting here.