Unit of Biostatistics, Epidemiology and Public Health

Department

Department of Cardiac, Thoracic, Vascular Sciences and Public Health

Main research activities/topics/projects

The Unit of Biostatistics, Epidemiology and Public health (UBEP), where the PhD curriculum is hosted, is a multifaceted research unit that encompasses a variety of specialized laboratories, each contributing to the overarching goal of advancing clinical research through methodological innovation, data analysis, and evidence synthesis. Below is a description of the research activities that can be carried out in the various labs within the UBEP:

-- Epidemiological Methods and Biostatistics:
Research activities in the lab focus on the development and application of advanced statistical methodologies tailored to biomedical research. Researchers in this lab can:
Develop and refine causal models to better understand the relationships between treatments, risk factors, and health outcomes.
Enhance propensity score methods to adjust for confounding in observational studies.
Create and test non-standard survival models that may better capture the complexities of time-to-event data.
Engage in modeling complex biological processes, including genetic and environmental interactions.

-- Clinical Epidemiology and Digital Health:

The lab serves as a hub for clinical epidemiology with a digital twist. Research activities here may include:
Designing and supporting clinical studies that incorporate digital health technologies, such as wearables and mobile health applications.
Analyzing data from electronic health records (EHRs) to identify patterns and predictors of health outcomes.
Evaluating the effectiveness of digital interventions in clinical settings.
Collaborating with interdisciplinary teams to integrate clinical insights with digital technology.

-- Artificial Intelligence for Medical Sciences:

The lab is at the forefront of incorporating AI into medical research. Potential research activities include:
Developing machine learning models to predict disease onset, progression, and treatment outcomes.
Applying natural language processing (NLP) techniques to mine insights from clinical narratives and literature.
Enhancing image recognition algorithms for diagnostic purposes in radiology, pathology, and other imaging-based disciplines.
Consulting on the ethical implications of AI in medical research and clinical practice.

-- Health Service Research:

The lab focuses on the evaluation and improvement of healthcare services. Research activities can encompass:
Assessing the efficiency and effectiveness of healthcare interventions and programs.
Investigating patient outcomes and satisfaction in relation to healthcare delivery models.
Conducting cost-effectiveness analyses of new healthcare technologies and practices.
Studying the impact of health policies on population health outcomes.

-- Ecological Statistics and Environmetrics:

The lab specializes in the intersection of environmental exposure and human health. Research activities here might involve:
Modeling the health effects of air pollution using advanced statistical techniques.
Conducting exposure assessment studies to quantify individual or population-level exposure to environmental hazards.
Collaborating with environmental scientists to understand the ecological determinants of health.
Developing predictive models for health outcomes based on environmental data.

-- Statistics in Experimental Sciences:

The lab is dedicated to the statistical aspects of experimental research in the life sciences. Research activities can include:
Designing experiments for in-vitro and in-vivo studies to ensure robust and valid results.
Analyzing data from biological and physiological experiments involving both animals and humans.
Consulting on the statistical feasibility of experimental research projects.
Applying advanced statistical techniques to experimental data to uncover underlying biological mechanisms.

-- Systematic Reviews and Meta-Analysis:

This cross-cutting activity supports all the laboratories in synthesizing existing research findings. Research activities can involve:
Conducting systematic reviews to aggregate evidence on specific clinical or public health questions.
Performing meta-analyses to quantitatively combine results from multiple studies.
Developing methods to assess the quality of evidence and address publication bias.
Providing guidelines and training on the conduct of systematic reviews and meta-analyses.
Each of these laboratories within the SCTB offers a unique set of research activities that collectively contribute to the advancement of clinical and biomedical research, leveraging statistical, epidemiological, and digital tools to improve health outcomes and healthcare services.

-- Health Science and Outcomes Research:

Analyzing patient-reported outcome measures (PROMs) to assess the effectiveness of health interventions from the patient's perspective.
Conducting health services research to identify barriers and facilitators to effective healthcare delivery.
Evaluating the impact of health literacy on health outcomes and the utilization of healthcare services.
Studying the role of interdisciplinary teams in managing complex health conditions and improving care coordination.
Investigating the social determinants of health and their influence on health disparities and outcomes.

Working language

English, Italian, Spanish (limited) 

Special entry requirements

Basic office/internet knowledge as a minimum requirement, database and/or statistical skills at any level preferred.

Duration in months (min-max)

Master Research:

PhD sandwich: 2-12

Post Doc: 2-12