CRSA – Postdoctoral in Leveraging AI for enhanced weather and climate prediction in Morocco

AboutUM6P:

LocatedintheheartofBenguerir’sfutureGreenCity,MohammedVIPolytechnicUniversity(UM6P)isaninternationallyorientedhighereducationinstitution dedicatedtodrivingdevelopmentin Morocco and across Africa.UM6Pfocuses on research and innovation to support education and sustainabledevelopment.Withstate-of-the-artinfrastructure,UM6Phasbuiltastrongacademic and research network and seeks to recruit high-quality professionals to enhance its research- focusedenvironment,basednearMarrakech.

AboutCRSA:

The Center for Remote Sensing Applications (CRSA) is an interdisciplinary research center within UM6P that spans multiple academic programs. CRSA focuses on addressing food and water security challenges in Africa, with a particular emphasis on the use of multi-source remotely sensed data. The center’s researchaimsto improvetheunderstandingofsurfaceprocessesandtheirinteractionswithclimateand humanactivities,withanemphasisonthesustainablemanagementofnaturalresources(soil,land,water, andagriculture)inthecontextofclimatechange.OneofCRSA’sprimaryobjectivesistoprovidedecision- support tools and services to local, national, and international users in water and food systems.

JobDescription:

Overthepastfewyears,advancesincomputationalpowerandtheincreasingavailabilityoflargevolumes ofremotesensingdatawithfinerspatialandtemporalresolutionshavesignificantlytransformedtheway weapproachclimateandweatherforecasting.Thesetechnologicaladvancementshavepavedthewayfor innovations, such as the integration of artificial intelligence (AI) into real-time data analysis. This integration can revolutionize the interpretation ofremote sensing data, allowingfor rapiddecision-making incriticalsituations,suchasduringnaturaldisasters.AImodels canprocess bigdatasets efficiently, helpingto make informed, unbiased decisions, and ensuring resources are distributed to those most in need. Additionally,whencombinedwithmodelingexperimentsorenhancedresearchinparameterization,AIis accelerating computational processes, improving prediction accuracy, and enabling the creation of extensive model ensembles at a reduced cost.

Inthiscontext,wearelookingforahighlymotivatedpostdoctoralresearchertojoinourteamattheCRSA to developAImodels,specificallydeeplearningapproaches,to analyzeandpredictkeyclimatevariables such as precipitation and temperaturewhich areessential for forecasting extreme events.These models will be applied to Morocco’s arid and semi-arid regions, aiming to produce more accurate predictions of droughts andfloods.Theseenhancedclimate andweatherpredictionswillcontribute tosafeguardingfoodproduction, ensuring proactive water management strategies, and reducing the health risks associated with extreme weather conditions, particularly in rural areas heavily reliant on agriculture.

KeyDuties

• Improve the accuracy of predicting climate variables like precipitation, temperature, and soil moisturebyleveraginglargemulti-sourcedatasetsfromremotesensing,IoTsensors,andclimate models.
• Design and implement deep learning models for forecasting extreme weather events such as floods, droughts, and heatwaves, integrating probabilistic approaches to account for uncertainties.
• Use data assimilation techniques to combine observational data with AI models, improving real time forecasting accuracy.
• Collaboratewithhydrologists,climatologists,anddatascientiststoensuremodelsarewell grounded in scientific understanding.
• Designandconductfieldworktovalidatemodelpredictionsandimprovetheperformanceofdeep learning approaches.
• Publishresearchfindingsinhigh-impactscientificjournalsandpresenttheresultsatinternational conferences.
• ContributetothesupervisionofMaster’sandPh.Dstudents.

Qualifications

• Ph.D.inArtificialIntelligence,DataScience,ClimateScience,Geoinformatics,AppliedandComputational Mathematics, or related fields.
• Proven experience indeveloping deeplearning models (e.g.,CNNs, RNNs, LSTMs) for large-scale environmental data analysis.
• Familiaritywiththeoreticalandpracticalaspectsofscientificdeeplearning;
• ProficiencyinprogramminglanguagessuchasPythonandR.
• Strongexperienceworkingwithclimateandremotesensingdatasetsforenvironmental applications.
• Experiencewithhigh-performancecomputingandanalysisoflargedatasets;
• Agoodtrackrecordofpublishedresearchinpeer-reviewedscientificjournals.
• Abilitytoworkinaninterdisciplinaryteamandcommunicatescientificresultseffectively.