PhD-position at the Sapienza University of Rome, Italy (ENDOTRAIN) (DC13)

PhD position

There is a vacancy for a PhD Research Fellow in AI-based virtual twins for monitoring, disease classification, and decision support in clinical practice (DC13) at the Sapienza University of Rome, Italy. The position is funded by the European Commission through the MSCA Doctoral Network Endotrain (Grant No: 101227148) and coordinated by the University of Bergen, Norway.

Supervisors:  Prof. Toni Mancini

Location: Sapienza University of Rome, Italy 

Duration: 3 years (with possibility of extension) 

Start date: August 2026 at latest

The students will be enrolled in the structured PhD programme  in Computer Science at Sapienza University of Rome, Italy: https://www.uniroma1.it/en/offerta-formativa/dottorato/2025/computer-science 

About the project/work tasks:

This position is part of:

19 PhD Fellowships available in Digital Endocrinology in the Marie Skłodowska-Curie Doctoral Network (ENDOTRAIN).Join Europe’s first doctoral network in digital endocrinology – integrating AI, sensor technology, omics, and clinical medicine to transform diagnosis and treatment of adrenal diseases. 

Digital medicine is entering a new era where human “digital twins” and sensor-based monitoring allow personalised diagnosis and treatment. ENDOTRAIN will train a new generation of interdisciplinary experts who merge clinical endocrinology, AI, data science, engineering, ethics and law into an integrated field of digital endocrinology. The programme focuses on adrenal disorders as a case study for advancing digital health in Europe.

This project is part of Work Package 3 (Trustworthy Data and Models) of the EU Horizon ENDOTRAIN doctoral training network. The recipient of this PhD position will carry out research activity at the Department of Computer science of Sapienza University of Rome, Italy (with secondments at University of Bergen, Norway and University of Ulm, Germany, see below). 

The envisioned research is aimed at developing novel Artificial Intelligence–based methods and software to assist physicians with:  

• Disease classification
• Treatment decision support
• What-if analyses. 

Although the developed methods and software will be general-purpose, a special emphasis will be put on the clinical domains of interest for the ENDOTRAIN network (endocrinology, with main focus on adrenal diseases). 

The envisioned activities will be oriented at developing hybrid data-driven/model-based AI methods to analyse time series of clinical data coming from sensors, enriched by the possible trajectories of relevant human patho-physiology models of interest for: 

• Phenotype classification
• Estimation of the probability of developing diseases
• Anomaly detection 
• Early diagnosis. 

The recipient will learn and apply a vast portfolio of complementary and synergic methods at the intersection of Artificial intelligence, Machine learning, Numerical simulation, Formal verification. Such methods include, among the others:  

• AI-guided simulation of the mathematical models of the patho-physiology and PK/PD of the pharmaceutical compounds of interest
• AI-based black-box optimisation
• AI-based synthesis of virtual twins of adrenal patients to simulate treatment outcomes 
• Synthetic data generation (virtual patients)
• Statistical model checking to ensure statistical correctness of the results
• Machine learning–based classification and regression methods 

The candidate will also design and develop new software and prototype models.  

Research areas: 

Computer science, Simulation-based automated synthesis and verification of human physiology models, Artificial intelligence, Machine learning 

Secondments: 

The candidate is expected to spend time at some of institutions partners of the ENDOTRAIN network, among which: 

• Computational Biology Unit, Department of Informatics, University of Bergen, Norway (under the co-supervision of Prof. Susanna Röblitz), to analyse pathophysiological models developed there
• Institute of Biomedical Engineering, University of Ulm, Germany (under the co-supervision of Prof. Walter Karlen), to develop interfaces for clinical data acquisition and personalised disease classification tools

Qualifications and personal qualities:

We are seeking highly motivated candidates with: 

• Master’s degree (or equivalent) in computer science or a related field
• Command in software design and development in high-level programming languages
• Knowledge in model-basedas well as data-driven artificial intelligence (symbolic AI and machine learning)
• Fluency in the English language, both written and spoken
• Strong interest in interdisciplinary research
• Good communication skills 

For further details, please visit our webpages: AI-based virtual twins for monitoring, disease classification, and decision support in clinical practice (DC13) and the programme webpage: Endotrain Doctoral Training Network | UiB

Salary and benefits

The position is an excellent opportunity for international networking at a pan-European level, industry exposure, and career development. 

The successful candidate will receive an attractive salary in accordance with the MSCA regulations for Doctoral Candidate DCs. The gross salary includes a living allowance (€  3821.53 per month), a mobility allowance of € 710 per month and, if applicable, a family allowance of € 660 per month. These amounts are nominal (gross) amounts and certain deductions will apply for social security contributions and/or taxes according to the applicable Italian national laws. The exact (net) salary will be confirmed upon appointment and is dependent on local tax regulations. 

Application procedure

All applications must be submitted via the Jobbnorge portal 

Your application must include the mandatory attachments from the ENDOTRAIN webpages - including "1. Application form" - "2. CV" - "3. Mobility declaration" - "4. Motivation Letter"

Eligibility (MSCA Doctoral Network rules)

• Applicants can be of any nationality. 
• Must not have resided or carried out a main activity in the host country for more than 12 months in the past 36 months before start of the PhD.
• Must hold a master’s degree (or equivalent) enabling doctoral studies.
• Must not already hold a doctoral degree.
• English proficiency required - transcripts of diplomas in English must be uploaded in Jobbnorge. 

In the "Jobbnorge-CV": Only fill in the basics of your 1) personal details, 2) short information about your degrees (in the field "Education / academic qualifications") - in order to minimise repetition with the CV attachment.

It is a condition of employment that the master's degree has been awarded (documentation must be provided). If you have not yet completed your master's degree, you can apply provided completion of the final master exam before the position start date. Please submit a statement from your institution confirming the expected date of award of your master's degree. 

For HR related questions contact the host institutions for the position you are applying.

General information

Contact

For questions about the project, please contact the primary supervisor Prof. Toni Mancini: tmancini@di.uniroma1.it

For questions about the ENDOTRAIN programme, please contact Programme Manager Elizabeth Farmer (elizabeth.farmer@uib.no) 

For HR-related questions, please contact HR-adviser Selina Hausberg (selina.hausberg@uib.no)

Diversity and inclusion

MSCA-Endotrain has a gender equality plan where gender balance among employees is therefore a goal. We encourage women to apply. If multiple applicants have approximately equivalent qualifications, the rules pertaining to moderate gender quotas shall apply. It is also a goal to recruit people with immigrant backgrounds. People with immigrant backgrounds and people with disabilities are encouraged to apply for the position. 

Information about applicants may be made public even if the applicant has asked not to be named on the list of persons who have applied. The applicant must be notified if the request to be omitted is not met. 

About MSCA Doctoral Networks

The MSCA Doctoral Networks aim to train creative, entrepreneurial, innovative and resilient doctoral candidates, able to face current and future challenges and to convert knowledge and ideas into products and services for economic and social benefit. The MSCA Doctoral Networks raise the attractiveness and excellence of doctoral training in Europe. Read More about the MSCA Doctoral Networks. 

For questions about the project, please contact the primary supervisor Prof. Toni Mancini: tmancini@di.uniroma1.it

For questions about the ENDOTRAIN programme, please contact Programme Manager Elizabeth Farmer (elizabeth.farmer@uib.no) 

For HR-related questions, please contact HR-adviser Selina Hausberg (selina.hausberg@uib.no)