AI-Driven Big Data Management and Workflow Optimization for Hyperspectral Full-time

About UM6P:

Located at the heart of the future Green City of Benguerir, Mohammed VI Polytechnic University (UM6P), a higher education institution with international standards, is established to contribute to the development of Morocco and the African continent. Its vision is honed around research and innovation at the service of education and development. This unique nascent university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high quality academics and professionals in order to boost its quality-oriented research environment in the metropolitan area of Marrakech.

About CRSA:

CRSA is a transversal structure across several UM6P Programs. Research within the center is organized around several major areas that aim to ensure the challenging Food and Water security goal in Africa, with a special focus on developing methods/tools that use multi-source remotely sensed data. The research aims to improve our understanding of the integrated functioning of continental surfaces and their interaction with climate and humans, with emphasis on sustainable management of natural resources (soil, land, water, agriculture) in the context of Climate Change. One of center’s goals is to provide a set of services and operational products to users (local, national and international) that aid in the decision support of water and food systems.

A dedicated and highly motivated PhD candidate is sought to join the research team at the Centre for Remote Sensing Applications (CRSA). The successful candidate will focus on developing AI-driven big data management and workflow optimization solutions for hyperspectral remote sensing. This research will be integral to advancing our project on leveraging hyperspectral remote sensing for soil fertility mapping and crop nutrient management in selected African nations. The candidate will work on designing and implementing AI and machine learning algorithms to automate data workflows, manage large datasets, and extract actionable insights from hyperspectral data, enhancing the efficiency and effectiveness of remote sensing applications.

Key Duties:

• Develop and implement AI-driven solutions for big data management in hyperspectral remote sensing.
• Design and optimize workflows for the automation of hyperspectral data processing and analysis.
• Apply machine learning algorithms to enhance the accuracy and efficiency of predictive models for soil and plant properties.
• Collaborate with IT specialists and remote sensing experts to integrate advanced data processing techniques.
• Conduct comprehensive evaluations to ensure the reliability and scalability of the developed systems.
• Disseminate research findings through publications in peer-reviewed journals and presentations at conferences and workshops.

Required Qualifications:

• Master’s degree in Computer Science, Remote Sensing, Geoinformatics, Data Science, or a related field.
• Strong background in artificial intelligence, machine learning, and big data management.
• Experience with hyperspectral data processing and workflow automation.
• Proficiency in programming languages such as Python or R, and familiarity with big data frameworks.
• Excellent analytical skills and attention to detail.
• Strong communication skills and the ability to work effectively in a multidisciplinary and international team environment.
• Enthusiasm for innovative IT solutions and hands-on research activities.

UM6P