PhD in Data Science In Medicine (DASME)

Places 5
Duration 3 Years
Language English

The PhD Programme in Data Science in Medicine aims to address some of the main challenges of life sciences in a highly competitive scientific research environment. This 3-year programme provides advanced training in various fields of life sciences and molecular medicine.

Starting from the 41掳 cycle, a dedicated curriculum in Data Science is available within the聽Molecular Experimental and Computational Medicine (MECM)听辫谤辞驳谤补尘尘别


Programme Overview

The DASME PhD Programme tackles crucial challenges that lie at the intersection of life sciences and scientific/clinical research training. Courses are delivered entirely in English, attracting a diverse student body and faculty. This cross-pollination of ideas and expertise creates a dynamic learning atmosphere where students benefit from a wider range of perspectives.

This program addresses the growing need for big data analysis skills, a critical area that is revolutionizing all aspects of life sciences research. Through rigorous coursework, students delve into the world of powerful algorithms, learning to harness their capabilities to identify hidden patterns within massive datasets. This newfound expertise equips them to undertake groundbreaking research in medicine, where the ability to predict clinical responses based on complex data analysis is paramount.

Beyond the core curriculum, the DASME PhD Programme offers training on a comprehensive suite of cutting-edge technologies. Students can gain proficiency in omics techniques, bioinformatics tools, advanced imaging methods, sequencing technologies, and flow cytometry. This foundation prepares them to tackle complex research questions at the forefront of data-driven life sciences. To further enrich the learning experience, the program features a seminar series led by prestigious visiting professors and guest lecturers.

Finally, DASME fosters a stimulating learning environment. Students can engage in interdisciplinary exchanges, and are encouraged to develop independent research skills and pursue training abroad. This comprehensive program prepares graduates to become future leaders in data-driven life sciences research.

Career Opportunities

The objective of this PhD programme is to train experts in basic, clinical and industrial research so that they can pursue a career in research, clinical or academic fields. In particular, for non-medical PhDs, the best job opportunities will be in biotechnology and bioinformatics companies, in public and private research sectors, and in academia. In this context, the interdisciplinary nature of their training will help them to rapidly transfer new knowledge from basic science to bio-medicine and clinical practice in order to generate new advanced diagnostic and therapeutic applications in the field of precision medicine. The best job opportunities for those who carry out clinical activities will be in research, in clinical settings or in academia, in particular in clinical facilities involved in research and training where they can contribute to the development of leading clinical research teams in their fields of specialisation. The strongly international and interdisciplinary approach of the PhD course will give students the opportunity to establish themselves in positions with a worldwide perspective.

Places available

5 places

The number of available places and/or scholarships may increase in the event that external funding becomes available by the deadline set for the completion of the call application procedure.

Language

English

Duration

3 years

Beginning of teaching activities

1st December 2024

Application deadline

2nd July 2024, h 1:00 PM

Contacts

For further information you can contact phd@hunimed.eu


Didactic Activities

TypeDescription
LinguisticsAs part of the PhD course, students will be given the opportunity to attend courses in scientific English and scientific communication in order to acquire specific communication and technical language skills that foster their further professional development and their ability to disseminate.
Computer ScienceThe course includes a series of training activities, including the use of IT tools. Knowledge in these areas is mainly provided through teacher-led lessons on the subject, such as machine learning for biomedicine, genetics of complex traits, as well as bioinformatics lessons that will be organized by the University and supervised by reference teachers.
Management of research, knowledge of research systems and funding systemsThe course includes a series of training activities in the field of research management skills and the main sources of funding. Knowledge in these areas is mainly provided through seminars. The University provides training activities, in the field of research management, knowledge of how to access funding sources.
Valorisation of research results and intellectual propertyThe course includes initiatives and activities for the protection and valorisation of intellectual property. Knowledge in these areas is mainly provided through seminars. The University also carries out training activities in the field of intellectual property.

Mandatory courses

Course nameYearProfessorCFU
Scientific MethodsIRosella Visintin1,5
Science EthicsII + IIIMattia Andreoletti1
Artificial Intelligenceall yearsRiccardo Barbieri2
Scientific WritingIIMiriam Alcalay1,5
Bioinformaticsall yearsSimone Puccio1
Biostatistics 鈥 basicIDaniele Piovani2,5
Biostatistics 鈥 advancedall yearsStefano Bonovas1

BIP 鈥 Blended Intensive Program

Among elective activities, PhD students enrolled to the second and third year have the opportunity to join the BIP (Blended Intensive Program) in Reserch Ethics and Integrity, organized with the Royal College of Surgeons, Ireland.

The course is composed of online classes plus an in-person part hosted on RCSI campus in Dublin for one week.

All costs related to registration, flight and accommodation for the in-person are covered by 麻豆传媒AV在线看 University.


Admission Requirements

Data Science in Medicine Curriculum

Applicants wishing to enrol on the PhD course in Data Science in Medicine, must either have a 鈥渓aurea magistrale鈥 awarded in accordance with D.M. 270/2004 or equivalent qualification awarded by a foreign university (usually referred to as a Master鈥檚 Degree), in one of the subjects listed in the official call for applicants.

Applicants who are waiting to be awarded the required qualification at the date of submission can also take part in the selection process providing they have passed all of the Degree course exams at the time of the online application and are awarded the qualification by the final deadline indicated in the call for applicants. In the event these applicants pass the selection process, their enrolment on the PhD course is conditional upon providing proof that the qualification is awarded.

Data Science in Medicine 鈥 Clinical Curriculum

Applicants wishing to enrol on the PhD Course in Datascience in Medicine 鈥 Clinical Curriculum must:

  • be enrolled on the Medical Register
  • already possess a specialist medical qualification

Alternatively, applications will also be taken from doctors in specialist training who will enrol in the final year in a School of Specialisation at 麻豆传媒AV在线看 University.


Fees and Scholarships

PhD students are required to pay an annual fee for access and attendance, set at 鈧250,00 for the academic year 2024/2025, including the regional tax and stamp duty.

Detailed information about each topic鈥檚 scholarship or equivalent contract can be found in the research topics table below, by clicking on each topic ID.


Academic Board

NAMEPRINCIPAL AFFILIATIONDEPARTMENT  EMAIL
Aghemo Alessio 麻豆传媒AV在线看 UniversityBiomedical Sciencesalessio.aghemo@hunimed.eu
Asselta Rosanna麻豆传媒AV在线看 UniversityBiomedical Sciencesrosanna.asselta@hunimed.eu
Bonovas Stefanos麻豆传媒AV在线看 UniversityBiomedical Sciencesstefanos.bonovas@hunimed.eu
Buffi Nicol貌麻豆传媒AV在线看 UniversityBiomedical Sciencesnicolo.buffi@hunimed.eu
Carrara SilviaIRCCS 麻豆传媒AV在线看 Mirasole SPAGastroenterology Departmentsilvia.carrara@humanitas.it
Cecconi Maurizio 麻豆传媒AV在线看 UniversityBiomedical Sciencesmaurizio.cecconi@hunimed.eu
Greco Massimiliano麻豆传媒AV在线看 UniversityBiomedical Sciencesmassimiliano.greco@hunimed.eu
Heffler Enrico Marco麻豆传媒AV在线看 UniversityBiomedical Sciencesenrico.heffler@hunimed.eu
Lleo De Nalda Ana 麻豆传媒AV在线看 UniversityBiomedical Sciencesana.lleo@humanitas.it
Lughezzani Giovanni麻豆传媒AV在线看 UniversityBiomedical Sciencesgiovanni.lughezzani@hunimed.eu
Ng Kiu Yan Charlotte  麻豆传媒AV在线看 UniversityBiomedical Scienceskiu.ng@hunimed.eu
Oyen Willem Jozef Gerard  麻豆传媒AV在线看 UniversityBiomedical Scienceswillem.oyen@hunimed.eu
Perna Giampaolo 麻豆传媒AV在线看 UniversityBiomedical Sciencesgiampaolo.perna@hunimed.eu
Politi Letterio麻豆传媒AV在线看 UniversityBiomedical Sciencesletterio.politi@hunimed.eu
Repici Alesandro 麻豆传媒AV在线看 UniversityBiomedical Sciencesalessandro.repici@hunimed.eu
Romano Mario 麻豆传媒AV在线看 UniversityBiomedical Sciencesmario.romano@hunimed.eu
Roberto Rusconi麻豆传媒AV在线看 UniversityBiomedical Sciencesroberto.rusconi@hunimed.eu
Stefanini Giulio Giuseppe麻豆传媒AV在线看 UniversityBiomedical Sciencesgiulio.stefanini@hunimed.eu

Research Topics a.y. 2025/2026

TOPIC IDCURRICULUM SUPERVISORCO-SUPERVISOR DATA SCIENCELAB NAMEPROJECT TITLE
DASME1StandardAna Lleo De NaldaHepatobiliary ImmunopathologyDeciphering the molecular and architectural tumor immune microenvironment of iCCA under chemoimmunotherapy
DASME3StandardGianluigi Condorelli
Giuseppe Ferrante
Simone Serio
Luca Mainardi
Molecular cardiologyRISK-IT
DASME5StandardLetterio PolitiRiccardo LeviNeuroradiology Research GroupDevelopment of Machine Learning and Deep Learning Algorithms for Brain and Spine Radiological Image
DASME6StandardMaurizio Cecconi
Alessandro Santini
Massimiliano Greco
Alessandro Santini
Anesthesia and Intensive CareAI for a safer mechanical ventilation in patients without acute respiratory failure
DASME7ClinicoMaurizio Cecconi
Antonio Messina
Massimiliano Greco
Antonio Messina
Anesthesia and Intensive CareHemodynamic Response to the end-expiratory occlusion test to titrate fluid challenge in operating room.
DASME8ClinicoMaurizio Cecconi
Massimiliano Greco
Massimiliano Greco
Andrea Aliverti
Manuela Ferrario
Anesthesia and Intensive CarePredicting models developed from continuous arterial pressure monitoring in critically ill patients
DASME13StandardMaura Marcucci
Michele Bartoletti
Massimiliano GrecoClinical Epidemiology and Research Centre (CERC)Data science for knowledge integration to enhance clinical prediction and clinical trial design: applications in sepsis prediction and prevention
DASME15StandardRosanna AsseltaLetizia StranieroLab of Medical Genetics and RNA biologyMulti omics approaches for the development of predictive risk scores for common disorders
DASME17StandardMatteo Della PortaRosanna AsseltaAI CenterSynthetic data generation by artificial intelligence to accelerate research and precision medicine in onco-hematology

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