This fully funded PhD position at Sapienza University of Rome offers an exciting opportunity to conduct cutting-edge research in Computer Science, focusing on Artificial Intelligence for Health. The project, part of the EU Horizon ENDOTRAIN MSCA Doctoral Network, centers on developing AI-based virtual twins for monitoring, disease classification, and decision support in clinical practice, with a special emphasis on endocrinology and adrenal diseases. Hosted by the Department of Computer Science and the Research lab in Artificial Intelligence for Systems Engineering (RAISE), the successful candidate will work on Work Package 3: Trustworthy Data and Models. The research involves designing hybrid data-driven and model-based AI methods to analyze clinical time series data from sensors, integrating human patho-physiology models for phenotype classification, disease probability estimation, anomaly detection, and early diagnosis. The project will leverage advanced techniques such as AI-guided simulation, black-box optimization, virtual twin synthesis, synthetic data generation, statistical model checking, and machine learning-based classification and regression. The PhD student will collaborate with leading European institutions, including secondments at the University of Bergen (Norway) and University of Ulm (Germany), gaining exposure to computational biology and biomedical engineering. The interdisciplinary nature of the ENDOTRAIN network ensures participation in workshops, retreats, transferable skills courses, and cohort-wide meetings across Europe, fostering international networking and career development. Eligibility requires a Master’s degree (or equivalent) in computer science or a related field, proficiency in high-level programming languages, expertise in both symbolic AI and machine learning, fluency in English, and a strong interest in interdisciplinary research. Candidates must not have resided or worked in Italy for more than 12 months in the 36 months prior to recruitment. Full-time commitment and active participation in network training are mandatory. The position offers a competitive salary package in line with MSCA regulations: a gross living allowance of €3821.53 per month, a mobility allowance of €710 per month, and a family allowance of €660 per month if applicable. These amounts are subject to deductions for social security and taxes according to Italian law. The appointment is for three years, with the possibility of extension, and includes full tuition and stipend support. Applications must be submitted via the Jobbnorge portal, including all required attachments. For further details, visit the project page and university links provided. The application deadline is February 15, 2026, with the latest possible start date in August 2026. This position is ideal for motivated graduates eager to advance AI methods for healthcare and contribute to impactful, interdisciplinary research in a vibrant European network.

This PhD Research Fellow position in AI-based virtual twins for monitoring, disease classification, and decision support in clinical practice (DC13) is offered at the Sapienza University of Rome, Italy, as part of the Marie Skłodowska-Curie Doctoral Network ENDOTRAIN. The project is funded by the European Commission and coordinated by the University of Bergen, Norway. The successful candidate will join a structured PhD programme in Computer Science and participate in a pan-European network focused on digital endocrinology, integrating artificial intelligence, sensor technology, omics, and clinical medicine to advance diagnosis and treatment of adrenal diseases. The research will develop novel AI-based methods and software to assist physicians in disease classification, treatment decision support, and what-if analyses, with a special emphasis on endocrinology and adrenal disorders. The project is part of Work Package 3 (Trustworthy Data and Models) and involves developing hybrid data-driven and model-based AI methods to analyze clinical time series data from sensors, enriched by human patho-physiology models. Key activities include phenotype classification, disease probability estimation, anomaly detection, and early diagnosis. The candidate will learn and apply a broad portfolio of methods at the intersection of artificial intelligence, machine learning, numerical simulation, and formal verification. Techniques include AI-guided simulation of mathematical models, black-box optimization, synthesis of virtual twins, synthetic data generation, statistical model checking, and machine learning-based classification and regression. The position also involves software and prototype model development. Secondments are expected at partner institutions: the University of Bergen (Norway) for pathophysiological model analysis, and the University of Ulm (Germany) for developing clinical data acquisition interfaces and personalized disease classification tools. The programme offers excellent opportunities for international networking, industry exposure, and career development. Applicants must hold a master's degree (or equivalent) in computer science or a related field, with skills in software design, high-level programming, and both symbolic and data-driven AI. English fluency is required. Candidates must not have resided in Italy for more than 12 months in the past 36 months before the PhD start date and must not already hold a doctoral degree. Diversity and inclusion are prioritized, with encouragement for women, people with immigrant backgrounds, and people with disabilities to apply. The position provides an attractive salary according to MSCA regulations: €3821.53/month living allowance, €710/month mobility allowance, and €660/month family allowance (if applicable), subject to Italian tax and social security deductions. The application deadline is 15th February 2026, and the latest start date is August 2026. Applications must be submitted via the Jobbnorge portal, including all mandatory attachments. For further details, visit the programme webpage or contact Prof. Toni Mancini.

The Sapienza University of Rome, Italy, in collaboration with the University of Bergen, Norway, and the University of Ulm, Germany, is offering a fully funded PhD Research Fellow position in AI-based virtual twins for monitoring, disease classification, and decision support in clinical practice as part of the Marie Skłodowska-Curie Doctoral Network (ENDOTRAIN DC13). This prestigious opportunity is embedded within a pan-European initiative to advance digital endocrinology, integrating artificial intelligence, sensor technology, omics, and clinical medicine to revolutionize the diagnosis and treatment of adrenal diseases. The successful candidate will join the Department of Computer Science at Sapienza University of Rome and be enrolled in its structured PhD programme in Computer Science. The research will focus on developing novel AI-based methods and software to assist physicians in disease classification, treatment decision support, and what-if analyses, with a special emphasis on adrenal disorders. The project is part of Work Package 3 (Trustworthy Data and Models) of the EU Horizon ENDOTRAIN network, aiming to create hybrid data-driven and model-based AI approaches for analyzing clinical time series data from sensors, enriched by human patho-physiology models. Key research activities include phenotype classification, estimation of disease probability, anomaly detection, and early diagnosis. The candidate will learn and apply a wide range of methods at the intersection of artificial intelligence, machine learning, numerical simulation, and formal verification. Techniques such as AI-guided simulation of mathematical models, black-box optimization, synthesis of virtual twins, synthetic data generation, statistical model checking, and machine learning-based classification and regression will be central to the project. The candidate will also design and develop new software and prototype models for clinical applications. Secondments are planned at the University of Bergen (Computational Biology Unit, Department of Informatics, under Prof. Susanna Röblitz) and the University of Ulm (Institute of Biomedical Engineering, under Prof. Walter Karlen), providing exposure to pathophysiological model analysis and clinical data acquisition interface development. Applicants must hold a master’s degree (or equivalent) in computer science or a related field, possess strong programming and software development skills, and demonstrate proficiency in both symbolic AI and machine learning. Fluency in English is required, and candidates should be highly motivated with a keen interest in interdisciplinary research. Eligibility rules include mobility requirements (not having resided in Italy for more than 12 months in the past 36 months), no prior doctoral degree, and documentation of English proficiency and degree completion. The position offers an attractive salary package in line with MSCA regulations: a living allowance (€3821.53/month), mobility allowance (€710/month), and family allowance (€660/month if applicable), subject to deductions for social security and taxes. The programme emphasizes diversity and inclusion, encouraging applications from women, individuals with immigrant backgrounds, and people with disabilities. Applications must be submitted via the Jobbnorge portal, including all mandatory attachments (application form, CV, mobility declaration, motivation letter, and degree documentation). For further details, visit the programme webpage or contact Prof. Toni Mancini ([email protected]). This is an excellent opportunity for international networking, industry exposure, and career development in a cutting-edge interdisciplinary research environment.