Postdoc Artificial Intelligence-Driven MOF Materials Discovery for Autonomous Humidity Control

Descrizione

Postdoc Artificial Intelligence-Driven MOF Materials Discovery for Autonomous Humidity Control Sintesi in italiano (traduzione automatica): L'organizzazione internazionale cerca un Ricercatore post-dottorato per un progetto sulla scoperta di materiali MOF guidata dall'intelligenza artificiale, focalizzato sul controllo dell'umidità ambientale. Il candidato lavorerà in un ambiente di ricerca collaborativo, affiancato da un dottorando, e avrà accesso a infrastrutture avanzate nell'ambito del programma prioritario France 2030 PEPR DIADEM AI-MAHC. Le mansioni principali includono l'uso di tecniche di screening computazionale ad alta capacità e modelli predittivi basati su machine learning per sviluppare nuovi adsorbenti d'acqua. È richiesta una laurea in ingegneria dei materiali, fisica o discipline affini, con competenze in machine learning e intelligenza artificiale. Work environment :C omputational work will be performed in strong collaboration with experimentalists expert in HT robot synthesis/characterization and advanced sorption techniques within the priority program France 2030 PEPR DIADEM AI-MAHC project (see for more details https://www.pepr-diadem.fr/projet/ai-mahc-2/ ). The Postdoc will work in tandem with a PhD student and will benefit from the PEPR DIADEM infrastructure, including advanced platforms, as well as from extensive scientific exchanges enabled by dedicated schools, workshops, and collaborative activities. Our research group: The successful candidate will join a strongly connected and international research team and collaborate with national and international academic partners. Our group is internationally renowned in the field of computational studies of MOFs (see for more information https://scholar.google.com/citations?hl=fr&user=QNfwyjgAAAAJ&view_op=list_works&sortby=pubdate Main mission : The overall objective of the project is to devise Artificial intelligence (AI)-driven strategy to discover a new generation of MOF water adsorbents with optimal indoor air humidity control performance by leveraging state-of- the-art high-throughput (HT) computational screening based on Machine-Learning Interatomic Potentials (MLIP), machine learning (ML) predictive models and AI tools. Activities : Computer science implying ML and AI tools applied to material science Annuncio in inglese. Fonte: Euraxess (Commissione europea).