International PhD Course in Molecular Medicine
Training course
Our PhD Program is aimed to provide outstanding interdisciplinary training in the broad area of Molecular Medicine. PhD students are expected to spend most of their time working on a research project under the direct supervision of a Director of Studies and with the external scientific advice of a Second Supervisor.
Each year, the PhD Course in Molecular Medicine offers a panel of courses that expose students to the most exciting and active research areas in the field and provide training in the transferable skills required for a successful career in academia and beyond. Training is delivered in English and covers the three-year duration of the PhD Course.
Students are expected to play an integral part in the life of our research community also taking advantage of the many lectures, workshops and seminars organized by the San Raffaele Scientific Institute.
Students may have the possibility to be involved in teaching and in supervising undergraduate students.
Training program a.y. 2022/2023
Please find below the list of seminars and courses for a.y. 2022/2023
Specific courses for each curriculum:
- An update on Multiple sclerosis and related immune-mediated disorders (Neuroscience and Experimental Neurology Curriculum)
- Epidemiological Methods for Medical Research (Experimental and Clinical Medicine Curriculum)
- Cell engeneering for cancer immunotherapy (for the others Curriculum)
Pitches, Posters, and PPT: Fundamentals of communicating science to peers - Prof. Armando Chapin Rodriguez
The Workshop aims to introduce the students to the foundations of effective scientific and technical communication, supported by findings from neuroscience, linguistics, and marketing. The theoretical part will be followed by practical exercises in small groups based on students’ own projects.
Computer improvement
The course aims to provide PhD students with methodological and technological knowledge on yìthe use of tools related to office automation, networking, cloud and cyber security. The course will cover the following topics: basic and advanced use of Microsoft Excel, advanced use of Microsoft Word, communication protocols and security protocols, basic elements of computer security, data protection and advanced cyber security techniques.
Problem solving logics - Prof. Enrico Dalla Rosa
Although we like to think that human beings are basically rational, it's easy to show that most people - even those who have a very high IQ - can make, in an easily predictable way, mistakes in solving even very simple problems. During the cycle of lessons we will try to vaccinate ourselves against these quite predictable biases, even if we will remain predictably irrational.
Research Integrity (parte I) - Dott. Roberto Buccione
The Research Integrity – General Principles seminar provides a basic overview of the core principles of research integrity, the definition of research misconduct and questionable research practice, general advice on dealing with the complex issues that can arise while planning, conducting and reporting research, and the functions and scope of the Research Integrity Office.
The primary verification of any scientific finding is its reproducibility, which however can occur only when all important steps can be retraced. They should therefore be documented with sufficient thoroughness that a person familiar with the subject would be able to reconstruct the experiments and considerations involved. The log/workbook a.k.a. the "lab book" (paper-based or digital) is the central repository for the logging of experimental protocols and procedures. The Care and Management of Laboratory Notebooks seminar provides a detailed overview of the current Ospedale San Raffaele and Università Vita-Salute San Raffaele regulations and general advice on the logging of experimentation and data in the lab books.
Statistical Methods in Biomedical Research
The course provides basic and advanced concepts for the collection, organization, and statistical analysis of data in the biomedical sciences. The course is divided into three modules:
Module 1 – Database construction and example description;
Module 2 - Inferential Statistics: from unchanged to multiple analysis;
Module 3 - Advanced statistical topics.
Participation in modules not by year of enrollment but by skills. A preliminary evaluation test is carried out online
Gender bias: a social-cognitive analysis
Notwithstanding the significant social progresses made in the last decades and the introduction of targeted political interventions, a male-female imbalance persists in modern Western societies. The consequence of this phenomenon, known as gender bias, have been studied at many different levels. For instance, women are underrepresented when it comes to higher leadership positions and numerous studies showed that gender bias in science disciplines and medicine is persistent today. Moreover, gender bias can be expressed in multiple ways, from more blatant to subtle manifestations, such as linguistic expressions adopted in everyday interactions.
Research in social cognition has shown that the roots of gender bias must be searched in the concept stereotype. Stereotypes are nothing else than labels that humans tend to attach to social entities and categories and that drive the way we think and behave. Following a social-cognitive approach, this course aims at providing a better understanding of gender bias by getting to know (i) what gender-stereotypes are; (ii) how they are formed and nourished by our society; (iii) what are their consequences; and (iv) what interventions can help dismantling them.
PhD students-invited lectures series
Career opportunities seminar series
Specific courses for each curriculum:
- An update on Multiple sclerosis and related immune-mediated disorders (Neuroscience and Experimental Neurology Curriculum)
- Epidemiological Methods for Medical Research (Experimental and Clinical Medicine Curriculum)
- Cell engeneering for cancer immunotherapy (for the others Curriculum)
Writing effectively about your research in papers and funding applications - Prof. Armando Chapin Rodriguez
The aim of the Workshop is to introduce students to the foundations of effective scientific and technical communication, supported by findings from neuroscience, linguistics, and marketing. The theoretical part will be followed by practical exercises in small groups based on students’ own projects.
Business Planning - Dr Giancarlo Monza
Research and development (R&D) of today is the medical practice of tomorrow. Unfortunately, the sustainability of R&D is at risk. Other highly innovative areas (e.g. aerospace industry, IT and also … the Army) have tried to addressed the issue of sustainability by enhancing their project planning capabilities.
During the lessons we will review the basic techniques of project planning, focusing on the peculiarity of R&D in health care, where ethics and patient-centric approaches are paramount. Practical examples of failed and successfully completed projects in healthcare will be presented and participant will also have the opportunity to discuss their own programs.
Research Integrity (parte II) - Dott. Roberto Buccione
The Research Integrity – General Principles seminar provides a basic overview of the core principles of research integrity, the definition of research misconduct and questionable research practice, general advice on dealing with the complex issues that can arise while planning, conducting and reporting research, and the functions and scope of the Research Integrity Office.
Research data management (RDM) is the effective and secure handling of information created in the course of research. Such information is typically the foundational evidence of published findings, grant reports, scientific posters, and other scholarly communications. Effective RDM spreads over a long lifecycle and continues well after the initial research has been published, and includes the materials, products, procedures, and other data sources that are part of any research project. The Research Data Management seminar aims to provide basic information on the principles of RDM, and to illustrate the importance of correct management, retrievability, preservation and storage of research data.
Statistical Methods in Biomedical Research
The course provides basic and advanced concepts for the collection, organization, and statistical analysis of data in the biomedical sciences. The course is divided into three modules:
Module 1 – Database construction and example description;
Module 2 - Inferential Statistics: from unchanged to multiple analysis;
Module 3 - Advanced statistical topics.
Participation in modules not by year of enrollment but by skills. A preliminary evaluation test is carried out online
The european research framework: policy, funding programmes and research management
The course aims to illustrate the characteristics of European and international research and to provide knowledge and tools for the management of research projects. In particular, the Horizon Europe programme will be developed. The structure of European projects and the rules for participation and management models will be analysed. Finally, the main design techniques will be presented in order to transfer tools and knowledge useful for developing a European research project.
PhD students-invited lectures
Career opportunities seminar series
Specific courses for each curriculum:
- An update on Multiple sclerosis and related immune-mediated disorders (Neuroscience and Experimental Neurology Curriculum)
- Epidemiological Methods for Medical Research (Experimental and Clinical Medicine Curriculum)
- Cell engeneering for cancer immunotherapy (for the others Curriculum)
Writing effectively about your research in papers and funding applications - Prof. Armando Chapin Rodriguez
The aim of the Workshop is to introduce students to the foundations of effective scientific and technical communication, supported by findings from neuroscience, linguistics, and marketing. The theoretical part will be followed by practical exercises in small groups based on students’ own projects.
Project assessment - Prof. Giovanni Navalesi
"And what happen if my scientific/clinical project is not going well? Shall we have some other opportunity or shell we throw on the basket what we have done?"
The course will be focused on how to evaluate the ongoing clinical/ scientific project in terms of GO/NO GO decision, the importance and to have in place techniques of risk based approach, risk planning and risk minimization measures for mitigating any unwanted deviations to the scientific target. On this regard, it will be highlighted the importance of Quality Systems (Standard Operating Procedures) applied to Clinical research project. And in case we should decide not to go ahead with the planned project, can we GO ahead with other different projects? Some examples of drugs that have been Repurposed after NO GO decisions from one clinical indication to another (i.e. Sildenafil) or example of molecules that are developed as Medical devices. The exemples include also drug potentially repurposing for Covid19 infection"
Research Integrity (parte III) - Dott. Roberto Buccione
The value and impact of scientific discovery would be very limited without the communication of findings to peers. Such communication may occur under many forms but most typically, as scholarly publications validated by peer-review. Authorship of research articles in scholarly journals is the most visible and direct form of academic recognition and credit. Funders, policymakers and institutions rely on the published record to identify the authors of scientific findings and their interpretation, and consequently to establish resource allocation, funding attribution, career progression and make hiring decisions. The Authorship and Conflicts of Interest seminar will provide essential information on the proper attribution of authorship, based on community-accepted rules and the current Ospedale San Raffaele and Università Vita-Salute San Raffaele guidelines for research integrity, and a breakdown of the responsibilities and rights associated with authorship. The seminar will also cover information on recognizing and dealing with financial and non-financial conflicts of interest in research.
The term “Open Science” indicates both the movement and the initiatives aimed at enabling full sharing of data and other results of scientific enquiry among peers and the other publics. Open Science therefore includes transparency in experimental methodology and in the observation, collection and publication of data, public availability and reusability of scientific data and finally, the widespread use of web-based tools to facilitate scientific dissemination, collaboration and outreach. The Open Science and Data Sharing seminar aims to provide basic knowledge on the burgeoning Open Science movement including the benefits and challenges of data sharing.
How to peer review scientific papers
The course offers a complete review of the mechanism of peer review (peer review) underlying the evaluation of the quality and merit of scientific manuscripts in order to obtain publication. The different approaches, methodologies and techniques of writing, ethical aspects, personal responsibilities and conflicts of interest will be presented and discussed. The course will also illustrate the editorial process and new models of scientific publishing.
Statistical Methods in Biomedical Research
The course provides basic and advanced concepts for the collection, organization, and statistical analysis of data in the biomedical sciences. The course is divided into three modules:
Module 1 – Database construction and example description;
Module 2 - Inferential Statistics: from unchanged to multiple analysis;
Module 3 - Advanced statistical topics.
Participation in modules not by year of enrollment but by skills. A preliminary evaluation test is carried out online
Open Science in practice: principles and tools for open access to scientific publications and research data
The Open Science approach includes all practices that promote accessibility and transparency at all levels of the research project lifecycle (data, methods, and publication). After discussing the core concepts and principles in Open Science, the course will provide practical information, guidelines and tools on how to make scientific publications and research data open to guarantee transparency, reproducibility and societal utility of scientific research.
Statistical methods in R
The course covers practical topics in coding with R. R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced.
The aim of the course is to show how R coding can be used to solve common issues encountered by neuroscientists.
The course will have a practical and interactive layout, with learning achieved mainly through presentation of real-life problems and solutions via hands-on activities
PhD students-invited lectures
Career opportunities seminar series
Training program a.y. 2023/2024
Please find below the list of seminars and courses for a.y. 2023/2024
Linguistic improvement Course - Scientific Communication
Informatic improvement Course
Specific courses for each curriculum - tbd
Problem solving
Research Integrity (part I)
Statistics Course
PhD students-invited lectures
Career opportunities seminar series
Linguistic improvement Course - Oral speachs and interview post PHD
Specific courses for each curriculum - tbd
Business Planning
Research Integrity (part II)
Statistics Course
The european research framework: policy, funding programmes and research management
Gender Medicine
Artificial Intelligence
PhD students-invited lectures
Career opportunities seminar series
Statistics
PhD student-invited lectures
Career opportunities seminar series
Linguistic improvement Course - Oral speachs and interview post PHD
Specific courses for each curriculum - tbd
How to peer-review scientific papers
Project assessment
Research Integrity (part III)
Statistics Course
Statistical methods in R
Open Science in practice: principles and tools for open access to scientific publications and research data
Artificial Intelligence
PhD students-invited lectures
Career opportunities seminar series