www.acad.jobs : academic jobs worldwide – and the best jobs in industry
                
     
Position: Research Associate candidate in Robust AI for flash flood prediction models
Institution: University of Luxembourg
Location: Luxembourg City, Luxembourg
Duties: Europe is facing an increasing number of flash flood disasters due to climate change. Due to prevailing land-use limitations hindering the application of traditional flood protection methods, innovative strategies are essential to effectively address risks associated with pluvial and fluvial flash floods. Artificial Intelligence (AI) presents unprecedented capabilities for predicting floods, assessing their impact, and facilitating timely activation of emergency response services. Despite the existence of state-of-the-art flash flood forecast models, it is crucial to ensure the robustness of the deployed models. In this context, robustness refers to the model's capacity to withstand unexpected disturbances, such as defective sensors or data drift, which could lead to mispredictions, and consequently result in incorrect emergency procedures. The Research Associate (RA) will be responsible for formulating, implementing, and evaluating a novel approach to enhance robustness
Requirements: A Computer Science background; Expertise in Machine Learning, Deep Learning; Good programming skills (python, Java…); Fluent written and verbal communication skills in English are mandatory; Commitment, team working and a critical mind
   
Text: Research Associate candidate in Robust AI for flash flood prediction models Europe is facing an increasing number of flash flood disasters due to climate change. Due to prevailing land-use limitations hindering the application of traditional flood protection methods, innovative strategies are essential to effectively address risks associated with pluvial and fluvial flash floods. Artificial Intelligence (AI) presents unprecedented capabilities for predicting floods, assessing their impact, and facilitating timely activation of emergency response services. Despite the existence of state-of-the-art flash flood forecast models, it is crucial to ensure the robustness of the deployed models. In this context, robustness refers to the model's capacity to withstand unexpected disturbances, such as defective sensors or data drift, which could lead to mispredictions, and consequently result in incorrect emergency procedures. The Research Associate (RA) will be responsible for formulating, implementing, and evaluating a novel approach to enhance robustness A Computer Science background; Expertise in Machine Learning, Deep Learning; Good programming skills (python, Java…); Fluent written and verbal communication skills in English are mandatory; Commitment, team working and a critical mind
Please click here, if the job didn't load correctly.







Please wait. You are being redirected to the job in 3 seconds.