Public Health Sciences
Doctoral programme (PhD)
A.Y. 2025/2026
Study area
Medicine and Healthcare
PhD Coordinator
The doctoral programme in Public Health Sciences aims to form researchers who are able to design, undertake and critically interpret research and advanced training projects and to assess health status and prevent the spread of transmittable and chronic-degenerative diseases within the population; promote health in individuals and populations; disseminate scientific culture and applicable research methodologies.
The internationalisation process foresees the exchange of students and professors with doctoral students, research centres and foreign institutions and the organisation of courses held by foreign experts.
The specific objectives of the doctoral programme include the development of research methodologies in the area of health, both laboratory and clinical; in the area of prevention policies focusing on the public and on particular groups at risk; in the context of services to the population for protecting and promoting individual health; in a transversal and transdisciplinary context that recognizes that the health of a populations is closely linked to that of animals and the environment ('one health' approach) and acquisition of a solid methodological grounding in the quantitative disciplines required to correctly apply and develop methods for the critical interpretation of basic, clinical, medical and epidemiological research findings.
The internationalisation process foresees the exchange of students and professors with doctoral students, research centres and foreign institutions and the organisation of courses held by foreign experts.
The specific objectives of the doctoral programme include the development of research methodologies in the area of health, both laboratory and clinical; in the area of prevention policies focusing on the public and on particular groups at risk; in the context of services to the population for protecting and promoting individual health; in a transversal and transdisciplinary context that recognizes that the health of a populations is closely linked to that of animals and the environment ('one health' approach) and acquisition of a solid methodological grounding in the quantitative disciplines required to correctly apply and develop methods for the critical interpretation of basic, clinical, medical and epidemiological research findings.
Tutte le classi di laurea magistrale - All classes of master's degree
Department of Clinical Sciences and Community Health - Via della Commenda 19 - 20122 Milano
- Website
https://discco.unimi.it/it/node/16663/ - Main offices
Dipartimento di Scienze cliniche e di comunità - Via Commenda, 19 - Milano - Doctoral programme coordinator: Parazzini Fabio
[email protected]
| Title | Professor(s) |
|---|---|
| Informed consent for clinical and research activities. Evaluations for quality and risk assessmet system | |
| Wastewater-based epidemiology: metagenomic approaches for monitoring antibiotic resistance in wastewater and surface waters.
Requirements: Knowledge in microbiology, molecular biology and epidemiology |
|
| Molecular epidemiology of antimicrobial resistance in a One-Health perspective. Sampling, sequencing and comparison of resistance genes from human and animal pathogenic bacteria in Lombardy.
Requirements: Knowledge in microbiology, molecular biology and epidemiology |
|
| Evaluation of predictive regression models with high-dimensional data. Model selection
Requirements: Good knowledge of statistical methods and survival analysis |
|
| Joint analysis of time to event data with longitudinal biomarkers data: applications in cardiology (NT-proBNP in patients with Surgical Ventricular Remodeling) and oncology (immunology in patients with metastatic melanoma)
Requirements: Basic knowledge of survival analysis |
|
| Use of generalized linear (and non-linear) models for treatment evaluation using clinically useful measures and time-to-event outcomes
Requirements: Good knowledge of statistical methods and statistical software |
|
| Effects of oxygen therapy on lung transplants and mortality in people with CF using multi state models
Requirements: Good knowledge of statistical methods and statistical software |
|
| Life expectancy in people with Cystic Fibrosis: comparison among european countries that joined the European Cystic Fibrosis Patients Registry using methods of relative survival
Requirements: Good knowledge of statistics and usage of statistical softwares |
|
| Models for growth charts in adolescents
Requirements: Knowledge of linear regression models and statistical software |
|
| Regression models time discrete survival analysis. Adjustment of the method in the presence of competing risks to estimate the sub-distribution hazard and marginal hazard
Requirements: good knowledge of statistical methods for survival analysis. Experience in programming with R language |
|
| Development of Machine Learning methdos for predictive models building
Requirements: Knowledge of multivariate analysis techiniques and modelling with penalized estimation |
|
| Phylogenesis and phylodynamics of the emerging infectious pathogens
Requirements: Expertise in the molecular biology techniques with special refer to the next generation sequencing and basic knowledge in bioinformatics and phylogenetic analysis |
|
| Early biomarkers of unilateral ureteropelvic junction obstruction in children: development of a laboratory model for their evaluation.
Requirements: Laboratory experience in cellular and molecular biology. Good knowledge of statistics |
|
| Multiomic approach to the study of Idiopathic Nephrotic Syndrome: clinical exome sequencing, epigenetic analysis, proteomic analysis and GC-MS.
Requirements: Laboratory experience in molecular biology and -omics. Good knowledge of statistics |
|
| Towards a more rational use of infertility treatments: studies on models validation, cost-effectiveness and cost-benefits
Requirements: Awareness on infertility clinical issues and good knowledge of statistics |
|
| Analysis of molecular data from Third Generation Sequencing of DNA and RNA for the evalutaion of bioprofiles in epigenetics
Requirements: Good experience in R programming. Good statistical knowledge |
|
| Multivariate analysis of envirnomental exposomic data
Requirements: Knowledge of the regression analysis, of the structural model analysis and of the multivariate statistical methods at an advanced level |
|
| Development of net and relative survival models for evaluating of incidence and mortality data from observational studies in clinical and environmental epidemiology.
Requirements: Good statistical knowledge |
|
| Effects of a diet adhering to the Mediterranean diet on the composition of breast milk
Requirements: Good programming skills in SAS or R. Good knowledge of basic statistics |
|
| A posteriori dietary pattern in nutritional epidemiology: problems of statistical analysis and epidemiological interpretation
Requirements: Good programming skills in SAS or R. Multivariate statistical knowledge |
|
| Issues of epidemiological models, with particular reference to large food or nutrient databases
Requirements: Good programming skills in SAS or R. Good knowledge of basic statistics |
|
| Infections of public health impact: epidemiology and prevention
Requirements: Basic knowledge of techniques used in virology |
|
| Use of routine data base to monitor the quality of the obstetric care and the analysis of the geographic and temporal trends of obstetric diseases
Requirements: Exerience in clinical research, public health and medicaal statistics |
|
| Clinical competence assessment frameworks in Health Care Organization and impact analysis | |
| Topics and methods for clinicians engagement in Health Care Organizations | |
| Organizational development and design in healthcare organizations: methods and tools for organizational check up and needs analysis, organizational models and structures design. | |
| Digital transformation in managing healthcare organizations: determinants and impacts | |
| Psychometric methodology in exposed to occupational stress
Requirements: Expertise in epidemiological studies with evaluation of psychological wellbeing in workers (health care or other sectors) |
|
| Shared and covariate-specific a posteriori dietary patterns for the assessemnt of reproducibility of dietary patterns across studies, countries, time, or major covariates
Requirements: Good programming skills in SAS or R. Multivariate statistical knowledge |
|
| Effects of environmental biodiversity in anthropic environments on the spread of vector-borne infections
Requirements: Knowledge of analysis methods using statistical models, vector sampling methods, and programming in R |
|
| Analysis of environmental drivers in the spread of antimicrobial resistance
Requirements: Knowledge of analysis methods using statistical models, of spatial information systems (GIS) and programming in R |
|
| Multispecies microbial resistome analysis by multiomics approach with nanopore sequencing, metaproteomics and high performance computing. Applications in public health
Requirements: Competences in microbiology and molecular omics techniques |
|
| Physiopathogenetic machanisms of occupatonal diseases | |
| Air pollution exposure and molecular markers
Requirements: Expertise in epigenetics, microbioma, or molecular biology |
|
| Environmental Exposure and Major Depressive Disorder
Requirements: Knowledge of main environmental exposures and health outcomes |
|
| Within the EPIGENESIS project, the effects of the exposome on health will be studied both at the individual and population level through the use of advanced "omics" technologies, such as epigenetics, metabolomics and single-cell RNAseq. The search for epigenetic biomarkers able to synthesize the complex information derived from the exposome will assume particular relevance
Requirements: Expertise in epigenetics, microbioma, or molecular biology |
|
| Projecting, implementing and assessing the effectiveness of nursing interventions in different clinical situations, in hospital and outpatient clinics. Projecting and implementing interventions for reducing nursing-related clinical risk
Requirements: Nursing competence (clinical, educational, organizational or researh-oriented) |
|
| Ageing and work: effects of workers' ageing and strenous working condition on biological age and work ability
Requirements: Skills in the field of the evaluation of health effect associated to occupational exposures |
|
| Prevention strategy in global health: mass vaccination, epidemiological surveillance and rapid response, monitoring of vaccine-preventable diseases, innovative screening. strategies
Requirements: Basic knowledge of epidemiology and prevention, experience in the molecular biology laboratory |
|
| Molecular epidemiology of viral infections of major public health impact
Requirements: Basic experiences in the molecular biology laboratory |
|
| Usage of big databases (administrative databases o more clinical databases togheter) to evaluate the ability (in terms of feasibility and accuracy) of the attribute matching methodology to predict the events risk in different clinical contensts, comparing prognostic scores already pubblished in literature
Requirements: Knowledge of medical statistic (base level) and good skills on using softwares for the statistical analysis and management of big databases (SAS, MS Access) |
|
| Statistical methods for primary studies and metanalysis on diagnostic accuracy
Requirements: Methods for contingency tables analysis and knowledge on linear model |
|
| Telemedicine: approaches and tools towards a value-based healthcare | |
| Operation management and service management in healthcare sector (patient flow logistics, patient experice) | |
| Co-production of health service | |
| Value based healthcare: approaches and tools | |
| Study of the role of diet in the development of various types of cancer, through statistical models capable of evaluating the simultaneous effect of a wide range of macro- and micronutrients.
Requirements: Programming skills in SAS or R languages |
|
| Analysis, interpretation and prediction of mortality and incidence data
Requirements: Knowledge of statistical programming languages SAS or R, and of the main analysis techniques used in this field (e.g., linear models and joinpoint) |
|
| Statistical models for the analysis of longitudinal data in clinical epidemiology: applications in cystic fibrosis and respiratory diseases
Requirements: Basic knowledge of generalized linear models. |
|
| Collaborative reanalysis of epidemiological data, including epidemiological inference
Requirements: Methods for meta- and pooled analyses, including mixed-effects models. Knowledge of SAS and R |
|
| Assessment of the benefits and harms of health interventions by conducting systematic reviews in different clinical areas (internal medicine, cardiology, oncology, neurology, orthopaedics and rehabilitation, public health).
Requirements: Background in biostatistics and public health. |
|
| Application of the principles, concepts and methods of evidence-based medicine to the world of medical information.
Requirements: Background in biostatistics and public health, and editing. |
|
| Health and work comfort 4.0
Requirements: Knowledge on the evaluation of professional risks and their effects on workers’ health and comfort |
Enrolment
Places available: 6
Call for applications
Please refer to the call for admission test dates and contents, and how to register.
Application for admission: from 15/05/2025 to 13/06/2025
Application for matriculation: from 14/07/2025 to 18/07/2025
Attachments and documents
Following the programme of study
Contacts
Office and services for PhD students and companies