Postdoc position in RNA Technologies Flagship – Foundation Models for RNA Regulatory Networks: from RNA-RNA Interactions to RNA-DNA Genome Regulation

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Postdoc position in RNA Technologies Flagship – Foundation Models for RNA Regulatory Networks: from RNA-RNA Interactions to RNA-DNA Genome Regulation Sintesi in italiano (traduzione automatica): L'Istituto Italiano di Tecnologia (IIT) cerca un ricercatore post-dottorato per il progetto RNA Technologies Flagship, focalizzato sull'applicazione di tecniche di machine learning e deep learning nelle scienze biologiche. La sede è presso l'IIT, e il candidato ideale avrà competenze in intelligenza artificiale, in particolare nell'applicazione del deep learning alla biologia strutturale. Le mansioni principali includono lo sviluppo di modelli predittivi per investigare il ruolo delle molecole di RNA nella regolazione genica e nelle malattie umane, collaborando con team multidisciplinari. È richiesta una laurea in biologia molecolare, genetica o biochimica, e familiarità con dati sperimentali complessi provenienti da studi omici o ricerche di laboratorio. È fondamentale avere una mentalità collaborativa per tradurre le intuizioni guidate dall'IA in applicazioni pratiche e cliniche. Postdoc position in RNA Technologies Flagship – Foundation Models for RNA Regulatory Networks: from RNA-RNA Interactions to RNA-DNA Genome Regulation - IT | Istituto Italiano di Tecnologia Postdoc position in RNA Technologies Flagship – Foundation Models for RNA Regulatory Networks: from RNA-RNA Interactions to RNA-DNA Genome Regulation Postdoc position in RNA Technologies Flagship – Foundation Models for RNA Regulatory Networks: from RNA-RNA Interactions to RNA-DNA Genome Regulation Step into a world of endless possibilities, together let’s leave something for the future! At IIT, we are committed to advancing human-centered Science and Technology to address the most urgent societal challenges of our era. We foster excellence in both fundamental and applied research, spanning fields such as neuroscience and cognition, humanoid technologies and robotics, artificial intelligence, nanotechnology, and material sciences, offering a truly interdisciplinary scientific experience. Our approach integrates cutting-edge tools and technology, empowering researchers to push the limits of knowledge and innovation. With us, your curiosity will know no bounds. We are dedicated to providing equal employment opportunities and fostering diversity in all its forms, creating an inclusive environment. We value the unique experiences, knowledge, backgrounds, cultures, and perspectives of our people. By embracing diversity, we believe science can achieve its fullest potential. Within the RNA Technologies Flagship Fondazione Istituto Italiano di Tecnologia (IIT) is seeking a highly motivated postdoc with a strong background in applying machine learning and deep learning techniques to the biological sciences. The ideal candidate will have expertise in artificial intelligence, with a specific focus on deep learning applications in structural biology. This is a unique opportunity to join a dynamic, interdisciplinary team operating at the intersection of computational genomics, RNA biology, and precision medicine. The goal is to build a strategic institutional resource for advancing discoveries in cancer, neurodevelopmental, and neurodegenerative disorders, through the integration of computational modeling of RNA and understanding RNA interactions. For more information about the RNA Technologies Flagship , visit: https://rna.iit.it/ The project aims to develop a new generation of artificial intelligence models to systematically investigate the role of RNA molecules in gene regulation and human disease. The central goal is to build a predictive framework capable of reconstructing and interpreting RNA-mediated interactions at genome scale by integrating large experimental, interactomic and multi-omics datasets. For RNA-RNA interactions, datasets generated by PARIS, RIC-seq, MARIO, KARR-seq and FANTOM-related approaches will be used to reconstruct RNA regulatory networks and uncover previously unknown, potentially functional interactions. In parallel, CLIP-seq and related datasets will be incorporated to model protein-RNA interactions and to place RNA-RNA contacts within the broader context of ribonucleoprotein regulation. These data-driven approaches will be complemented by novel computational developments designed to improve interaction prediction, prioritization and biological interpretation. The ideal candidate has a strong background in molecular biology, genetics, and biochemistry, and is familiar with complex experimental data generated from omics studies or laboratory-based research. A collaborative mindset is essential, as the role involves working closely within multidisciplinary teams of biologists, chemists, engineers, and medical professionals, with the goal of translating AI-driven insights into practical and potentially clinical applications. The project will extend beyond classical RNA interactions to include RNA-chromatin and RNA-DNA associations. In th