Training course Università Vita-Salute San Raffaele

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.

First year

Second year

Third year

First year

Courses curriculum-specific:

Targeting RNA-binding proteins in neuronal degeneration and repair (NEN)

RNA-binding proteins (RBPs) play essential roles in neuronal development, function and maintenance by precisely controlling all aspects of mRNA regulation, including alternative splicing, stability, trafficking and translation. It is now clear that various neurological disorders are linked to aberrant RBP function and localization, and targeting this group of proteins could represent an attractive therapeutic strategy to prevent neuronal loss and/or promote neural repair. This course will provide an overview of the most recent advances in RBP functions in neural repair after injury as well as the latest evidence showing how targeting RBPs could represent an effective new avenue for treating neurodegenerative disorders.

Pluripotent stem cells and next generation therapies (GCT)

The advent of pluripotent stem cells has revolutionized the landscape of regenerative medicine. We will embark on this transformative journey with our cutting-edge PhD course focused on Pluripotent Stem Cells and Next-Generation Therapies. We will delve into how pluripotent stem cells can be harnessed to design and test new therapeutic approaches, exploring their unique ability to differentiate into diverse cell types. The program will cover the latest advancements in stem cell research, including CRISPR-based genome editing and synthetic biology approaches and will emphasize translating scientific insights into innovative therapies, fostering a deep appreciation for the ethical and regulatory dimensions of stem cell applications.

Molecular mechanisms of drug resistance in cells (CMB and BAIO)

In this course, students will gain a better understanding of molecular processes that cells imply to adapt to therapies and evade death. In details, the course will be dived into three sessions to have an overview about i) innovative quantitive methods to probe drug resistance; ii) epidemiology and evolution of resistance mechanisms in microorganisms, and iii) acquired resistance mechanisms to targeted therapy and immunotherapy. Besides learning about Molecular mechanisms of drug resistance in cells from experts in the field, students will have the opportunity to further discuss with the speakers about these topics by preparing a frontal lesson and explore career path options to undertake after the completion of their predoctoral studies.

Quantitative biomarkers in translational research (ECM)

Communicating research: Short oral presentation - Embo Solutions

In this workshop, EMBO Press editors work with PhD students on the principles, practicalities and strategies of scientific publication. The workshop is focused on how to effectively present your work in a short oral form in various contexts - e.g. poster presentation, flash talk or elevator pitch. The course includes a balanced combination of theory presentation, group work, and interactive discussions to keep the participants engaged.

IT course - Dr. Lorenzo Cibrario

The course aims to provide PhD students with methodological and technological knowledge on the 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.

Research Integrity (parte I) - Dr. 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 course provides a detailed overview of the current regulations and general advice on the logging of experimentation and data in the lab books.

Gender Equality - Dr. Simone Mattavelli – Dr. Monica Fabbri

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.
Finally, the course will include an in-depth analysis dedicated to the "Gender Equality Plan" approved by UniSR.

Statistical methods in R - Dr. Arianna Sala

The course covers practical topics in coding with R. The aim of the course is to show how R coding can be used to solve common issues encountered by neuroscientists. The course will provide a basic introduction to R, covering data management, statistical modelling and data visualization. Elements of scripting will be introduced. 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.

Problem Solving Logics - Dr. Enrico Dalla Rosa

The focus of this class is human error. Our species did a good job in surviving the evolution lottery, thanks also to a good ability in avoiding - as a whole - fatal mistakes. But the growing complexity of the world makes it more and more important avoiding mistakes that can have dire consequences, particularly in some domains – medicine is one of them.
Although we like to think that, when facing challenging situations, we 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, relevant mistakes. During the cycle of lessons, we will try to vaccinate ourselves against some of the quite predictable biases that push us to do mistakes even we try as carefully as we can to avoid doing so.

PhD inter disciplinary seminars

Today more than ever, scientific research is a complex endeavor that requires wide knowledge outside of the specific context to produce impactful outcomes and help researchers thrive in a highly competitive environment.
This course was created by initiative of the Pro-Rector for scientific research and students together with the Research Policy Office (RPO) to discuss interdisciplinary themes, from the social impact of science to how to handle high-pressure workloads.
The aim is to stimulate critical, out of the box, thinking. The course will feature 3 seminars held by external experts, selected by a committee of PhD students from all 3 courses, coordinated by Monica Fabbri (RPO).

Diving into the data management plan (DMP) and IRIS - Dr. Silvia Corbetta and Dr. Marco Soriano

This course will discuss two essential research tools. The first part will focus on the DMP, i.e., a structured document which outlines all aspects of the research data lifecycle (e.g., data organisation and curation, adequate provisions for their preservation and sharing). Writing a DMP will address in advance all needs/challenges that are likely to be encountered over the course of a research project, and it is considered best practice, as it makes work more efficient and contributes to the long-term preservation of data. After introducing the typical components of a DMP practical information will be provided on how to address them. Furthermore, though the Q&A session students will have the chance to discuss the challenges their facing and clarify any doubt about their DMP.

The second part of the course will focus on the UniSR IRIS. After introducing the core concepts and principles in Open Access to publications, practical information will be provided on how to use IRIS for depositing, collecting and disseminating the publications.

PhD students-invited lectures

The PhD student-invited lectures are seminars organized by a PhD Student Committee, composed of students from different research areas. The Committee selects and invites 3-4 international scientists each year. The invited scientists give lectures open to all institute members, and then dedicate a considerable amount of time to discuss with PhD students both about their research and more general topics, such as the pathway to becoming an independent researcher, etc. The PhD student-invited lectures offer students the opportunity to interact with top scientists in an informal environment and improve their networking skills, which are crucial in scientific research.

Career opportunities seminar series

The "Career Opportunities Seminar Series" aims to promote career prospects and professional opportunities for PhD students in the fields of research and related sectors, both public and private. The wide variety of potential career paths that PhD students can aspire to requires an understanding of the available opportunities.To promote this understanding and to create useful contacts with the working world, various seminars are organized by prominent professionals in different fields of interest, coming from both academic and corporate backgrounds. The seminars typically include a brief overview of the speaker's career path leading to their current position, a description of their activities, and finally, a phase of individual or group interviews with PhD students.

Second year

Courses curriculum-specific:

Targeting RNA-binding proteins in neuronal degeneration and repair (NEN)

Pluripotent stem cells and next generation therapies (GCT)

Molecular mechanisms of drug resistance in cells (CMB and BAIO)

Quantitative biomarkers in translational research (ECM)

Communicating research: Writing a paper - The editorial process - Embo Solutions

In this workshop, EMBO Press editors work with PhD students or Postdocs on the principles, practicalities and strategies of scientific publication. Topics covered include understanding the structure and content of a manuscript, assembling figures and writing effective titles and abstracts. The participants will also learn to navigate the editorial process at journals.
The course includes a balanced combination of theory presentation, group work, and interactive discussions to keep the participants engaged.

Research Integrity (parte II) - Dr. Roberto Buccione

The value and impact of scientific discovery would be very limited without the dissemination of findings to peers. Such communication may occur under many forms but most typically, as scholarly publications validated by peer-review. The course will illustrate the editorial process, the evolution of the current publishing paradigm, the emerging publishing models, and the dark side of publishing.

Gender Medicine - Dr. Cinthia Farina and Prof. Alaide Chieffo

Historically, medicine and biology have been developed using an androcentric approach, generalizing results to females and restricting sex differences to reproductive issues only. The course “Gender Medicine” will provide an introduction to the next-generation medicine, explain definitions, highlight normative references and resources, and discuss examples and implications for health research and services.

Writing Successful Fellowship Applications - Dr. Thiago Carvalho and Dr. David del Álamo (Fellowsherpa)

For many early career researchers, writing a fellowship application will be their first experience with the highly competitive scientific funding system. Fellowsherpa’s two-day interactive course exposes participants to some of the most prestigious international fellowships, including the Marie Skłodowska-Curie, EMBO, and Human Frontier Science Program postdoctoral programs.

The european research framework: policy, funding programmes and research management - Dr. Federica Prete – Dr. Maya Fedeli

The course aims to understand the journey from call topic, developing a project idea, writing a proposal to submission within the Horizon Europe and to provide knowledge and tools for the development of EU research projects. Moreover, the course will present Horizon Europe main features and the ERC and the Marie Curie Programmes. Finally, the course will introduce Citizen Science and how to integrate the this innovative approach into research projects.

Statistical methods in biomedical research - Prof. Paola Rancoita and Prof. Chiara Brombin

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 two modules:

MODULE 1: Inferential Statistics: comparison among groups and bivariate analysis.
MODULE 2 : Modelling the relationships between variables

Participation in modules not by year of enrollment but by skills.

Statistical methods in R - Dr. Arianna Sala

The course covers practical topics in coding with R. The aim of the course is to show how R coding can be used to solve common issues encountered by neuroscientists. The course will provide a basic introduction to R, covering data management, statistical modelling and data visualization. Elements of scripting will be introduced.
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.

Business Planning - Dr. Giancarlo Monza

During the conversations we will review the basic techniques of project planning and team (=people) performance to minimize / prevent human errors, 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.

Fundamentals of AI in medicine - Prof. Carlo Tacchetti

Artificial Intelligence (AI) is gaining more and more popularity in healthcare. Technologies enabling automation of time-consuming clinical tasks or clinical decision support systems based on machine learning, a branch of AI, will potentially improve cancer care. Nevertheless, the unconscious use of such algorithms, often developed outside the clinical domain, without involving the healthcare professionals will reduce the clinical impact, creating mistrust in AI. We will introduce to young clinical researchers the foundations of AI including an overview on major ML algorithms and their applications with healthcare data, design of clinical studies involving the development of AI algorithms, and privacy/ethical issues related to the usage of AI algorithms in a hospital.

PhD inter disciplinary seminars

This course was created by initiative of the Pro-Rector for scientific research and students together with the Research Policy Office (RPO) to discuss interdisciplinary themes, from the social impact of science to how to handle high-pressure workloads.

The aim is to stimulate critical, out of the box, thinking. The course will feature 3 seminars held by external experts, selected by a committee of PhD students from all 3 courses, coordinated by Monica Fabbri (RPO).

PhD students-invited lectures

Career opportunities seminar series

Follow up data management plan (DMP) - Dr. Silvia Corbetta and Dr. Marco Soriano

This follow-up course aims at providing feedback on the DMPs submitted by the students and discuss common issues identified during the review process. The course also offers the opportunity to clarify any questions or uncertainties regarding the topics addressed in the submitted DMPs and provides clarifications on the features of our institutional repository IRIS.

Third year

Courses curriculum-specific:

Targeting RNA-binding proteins in neuronal degeneration and repair (NEN)

Pluripotent stem cells and next generation therapies (GCT)

Molecular mechanisms of drug resistance in cells (CMB and BAIO)

Quantitative biomarkers in translational research (ECM)

How to review scientific papers - Embo Solutions

In this workshop, EMBO Press editors work with PhD students on the principles and practicalities of peer review. Topics covered include the key elements of good peer review and the role of peer review in publishing reproducible science. We also discuss ethical considerations such as conflicts of interest and give guidelines to young scientists about how to become good reviewers.
The course includes a balanced combination of theory presentation, group work, and interactive discussions to keep the participants engaged.

Research Integrity (parte III) - Dr. Roberto Buccione

Investigators have a general responsibility to contribute to science outreach and popularisation because they accomplish the high purpose of making research findings accessible to a non-expert audience, who might benefit from the information. Such activities also express the spirit of Responsible Research and Innovation (RRI). The course will show the pivotal importance of science communication in the career of a scientist. It is designed to enhance the communication skills of PhD students, understanding how to convey the complex scientific concepts of research to a wider audience in a clear, engaging, and accessible manner. During the course, students will gain an understanding of science communication strategies, learn to translate technical language into a format understandable by the general public, and hone their skills in the use of different communication platforms and tools.

Open Science in practice: principles and tools for open access to scientific publications and research data - Dr. Silvia Corbetta - Dr. Marco Soriano

The Open Science approach includes all practices that promote accessibility and transparency at all levels of the research project lifecycle. This course will introduce the core concepts and principles in Open Science (e.g., open access, data sharing) and provide guidelines and tools on how to make scientific publications and research data open, to guarantee reproducibility and societal utility of scientific research. Furthermore, practical information will be provided on how to use the institutional repositories for publications (IRIS) and data (ORDR).

Statistical methods in biomedical research - Prof. Paola Rancoita and Prof Chiara Brombin

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 two modules:

MODULE 1: Inferential Statistics: comparison among groups and bivariate analysis.
MODULE 2 : Modelling the relationships between variables

Participation in modules not by year of enrollment but by skills.

Statistical methods in R - Dr. Arianna Sala

The course covers practical topics in coding with R. The aim of the course is to show how R coding can be used to solve common issues encountered by neuroscientists. The course will provide a basic introduction to R, covering data management, statistical modelling and data visualization. Elements of scripting will be introduced.
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.

Project Assessment - Dr. Gianni Navalesi

And what happens if my scientific/clinical project is not going well? Shall we have some other opportunity, or shall we throw on the basket what we have done? We will focus on evaluating the importance of having at hand techniques of risk based approach, risk planning and risk minimization measures. These tools are aimed at mitigating any unwanted deviations from the scientific target.

In this regard, it will be highlighted the importance to have in mind other potential solutions in the case that the primary target could not be achieved. We will discuss some examples of drugs that have been repurposed from one clinical indication to another (i.e. Sildenafil),as well as the opportunity to switch to other fields such as Medical Devices or Food supplement

Fundamentals of AI in medicine - Prof. Carlo Tacchetti

PhD inter disciplinary seminars

PhD students-invited lectures

Career opportunities seminar series

First year

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

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

Second year

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

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

Third year

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

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

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International PhD Course in Molecular Medicine

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