DASMEN (Data Science in Medicine and Nutrition) PhD Programme
The DASMEN (Data Science in Medicine and Nutrition) PhD Programme addresses challenges in the life sciences field and in the scientific and clinical research training field. The PhD has an international dimension because of its structure, the course is held in English, for enrolled non-Italian PhD students and for the involvement of foreign teachers. Part of the training activities are carried out within European projects.
Characteristic of the DASMEN PhD is the partnership between universities and structures more suited to applied research (IRCCS Humanitas, companies in the field of life sciences and information technology) and basic research (Humanitas Research and University of Milan-Bicocca). The PhD takes up the challenge of recent years to analyze a large amount of data (big data) in a systematic way by means of effective algorithms, in order to find common elements, in an attempt to predict the clinical response from the view point of medicine and precision nutrition. The PhD offers specific training on enabling technologies, such as homics, bioinformatics, imaging, sequencing and flow cytometry. The training is enriched by seminars held by foreign lecturers (Visiting Professor, Guest Lecturer). The course provides a stimulating environment through the organization of Journal clubs, informal exchanges between disciplines, encouragement of researcher independence and training abroad.
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.
|PhD Coordinator: Prof Rosanna Asselta|
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.
|Beginning of the academic year
1st November 2021
|Call for applications 2021 (EN)|
|Linguistics||As 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 Science||The 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 systems||The 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 property||The 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.|
Applicants wishing to enrol on the PhD course in Datascience in Medicine & Nutrition, must either have a “laurea magistrale” awarded in accordance with D.M. 270/2004 or equivalent qualification awarded by a foreign university (usually referred to as a Master’s 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.
Applicants wishing to enrol on the PhD Course in Datascience in Medicine & Nutrition, DASMEN-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 Humanitas University
Doctors in specialist training who are already enrolled in the final year of Specialisation at any university and who will complete their training by October 31st 2021. In the event these applicants pass the selection process, they may conditionally enrol on the PhD Course and are required to provide proof of the awarded qualification by the beginning of academic activities.
Fees and Scholarships
PhD students are required to pay an annual fee for access and attendance, set at €250,00 for the academic year 2021/2022, including the regional tax and stamp duty.
Detailed information about each topic’s scholarship or equivalent contract can be found in the research topics table below, by clicking on each topic ID.
How to Apply
- Registration or access with your LOGINMIUR credentials
- Application form submission
- Payment of the application contribution
The application form must be completed in all its parts, on penalty of exclusion. In particular, applicants must submit all of the following documents in PDF format:
- Curriculum vitae
- Motivation letter
- Copy of a valid ID or passport (for Non-EU citizens)
- Diploma Supplement
- Copy of the receipt of payment of €30,00
Additionally, applicants may indicate name and contacts of maximum two referees, preferably chosen among those who have had a supervising role of the candidates. The referees will be directly contacted by Humanitas University and asked to complete a brief letter of reference.
Further details about the application procedure will be reported in the official call for applicants.
Admission to the PhD Programme is based on a public selection process consisting of
- the comparative evaluation of the titles and qualifications and
- an interview carried out in English by a Committee composed of a maximum of seven members.
The aim of the selection process is to assess the knowledge, competencies and aptitude of the applicants for scientific research as well as their motivation for undertaking the PhD programme.
Prior to the interview, applicants may be asked to take a multiple-choice test, aimed at assessing the applicant’s specific knowledge in the fields of the research projects of the Campus.
A good knowledge of English is required and will be tested during the interview.
Should reasons justify it, the test and interview can be conducted via video-conference. Those who intend to conduct the interview via video-conference or request special assistance should specify this on the application form.
PhD Coordinator: Professor Rosanna Asselta
|Alessio Aghemo||Humanitas Universityemail@example.com|
|Nicolò Buffi||Humanitas Universityfirstname.lastname@example.org|
|Ferdinando Cananzi||Humanitas Universityemail@example.com|
|Stefanos Bonovas||Humanitas Universityfirstname.lastname@example.org|
|Giorgio Walter Canonica||Humanitas Universityemail@example.com|
|Maurizio Cecconi||Humanitas Universityfirstname.lastname@example.org|
|Matteo Donadon||Humanitas Universityemail@example.com|
|Ana Lleo De Nalda||Humanitas Universityfirstname.lastname@example.org|
|Silvia Carrara||Istituto Clinico Humanitasemail@example.com|
|Giampaolo Perna||Humanitas Universityfirstname.lastname@example.org|
|Giulio Stefanini||Humanitas Universityemail@example.com|
|Politi Letterio||Humanitas Universityfirstname.lastname@example.org|
|Asselta Rosanna||Humanitas Universityemail@example.com|
|Alesandro Repici||Humanitas Universityfirstname.lastname@example.org|
|Mario Romano||Humanitas Universityemail@example.com|
|Giovanni Lughezzani||Humanitas Universityfirstname.lastname@example.org|
|Wim Oyen||Humanitas Universityemail@example.com|
|Lorenza Rimassa||Humanitas Universityfirstname.lastname@example.org|
|Rita De Sanctis||Humanitas Universityemail@example.com|
|Enrico Heffler||Humanitas Universityfirstname.lastname@example.org|
|Marco Antoniotti||Università Bicocca||Marco.email@example.com|
|Vincenzo Bagnardi||Università Bicoccafirstname.lastname@example.org|
|Davide Bernasconi||Università Bicoccaemail@example.com|
|Roberto Rusconi||Humanitas Universityfirstname.lastname@example.org|
|Topic ID||Project Title||Curriculum||Research Supervisor||Clinical Supervisor||Co-Supervisor Data Science|
|DASMEN 1||Evidence Synthesis in Inflammatory and Immunodegenerative Diseases||Standard||Stefanos Bonovas||Daniele Piovani|
|DASMEN 2||Development of computational approaches in Flow Cytometry and Next Generation Sequencing to investigate on the pathogenesis of unprovoked venous thromboembolism||Standard||Roberto Rusconi||Rocco Piazza
|DASMEN 3||Contrast-Enhanced Spectral Mammography in Women With Personal History of Breast Cancer||Clinico||Rosanna Asselta||Arturo Chiti
|DASMEN 4||Technical implementation of Artificial Intelligence algorithms to automate the Total Marrow Lymph-nodes Irradiation||Standard||Roberto Rusconi||Pietro Mancosu
|DASMEN 6||Methods and tools for the integration of clinical/epidemiological data and multi-omics data||Standard||Vincenzo Bagnardi
|DASMEN 7||New models for patient management in the Emergency Department: looking for improvement of efficiency and quality.||Standard||Ana Lleo
|DASMEN 8||Multimodality imaging and artificial intelligence for vulnerable plaque characterization||Standard||Giulio Stefanini