During the first three weeks of the semester, we organise refresher courses on certain topics needed to follow classes: Mathematics, Physics, Biochemical Modeling, Evolution, Matlab, and R.

Since our students come from different scientific backgrounds, the classes proposed during the Bootcamp make them aware about which subjects they should start working on their own. Typically, a student with a physics background needs to work on fundamental biological concepts such as central dogma, evolution, DNA, methods in biology, while a biologist usually needs to focus more on the mathematical and physical concepts that are used in the quantitative description of living systems.

Teachers: Wolfram Liebermeister (INRAE), Matthieu Jules (INRAE), François Bertaux (Pasteur)

Overview of the course: Systems biology is an attempt to understand cells (or other biological systems) as complex systems by studying their basic building blocks and their interactions, and connecting this reductionist view with a holistic, systemic perspective. To understand biological functions, it often does not suffice to study single proteins, single genes, single cells, or single organism. Rather, the ability of living matter to perform amazing tasks relies on an ensemble of actors acting collectively. Those tasks, involving for example decision making or information processing, can thus be understood only at the system level. The course will be grounded in quantitative biology and modeling motivated by examples coming from biological systems. In addition, we present some basic concepts of statistical physics and engineering that have been successful in solving such problems in other disciplines, and will show how they apply to the description of biological systems.

Course syllabus:

• Introduction to Systems Biology
• High-throughput experiments - the omics revolution
• Gene expression regulation and noise
• Structure and function of biological networks
• Cellular resource allocation and growth
• Compromise, competition and cooperation
• Population dynamics and evolution

Course objectives:

• Gain knowledge about cells, cellular processes, and methods to study them.
• Be able to describe biological systems at the system level as a list of units and their interactions, or as a combination of modules, and the resulting dynamics.
• Become familiar with basic concepts of theoretical systems biology such as uncertainty, optimality, modularity, or robustness.

Teachers: Jake Wintermute (CRI), Radek Ejsmont (CRI)

Overview: Synthetic Biologists work to design and create biological systems that are scientifically interesting or technologically useful. Synthetic Biology adapts concepts from the physical and information sciences, seeking to become a fully rational framework for the engineering of life. This course will introduce the major trends that drive the Synthetic Biology literature. Whenever possible, we will identify the fundamental theories and practices that unify the field and provide a foundation for future projects. Students will confront an emerging domain with an unclear definition, vague boundaries, and boundless ambition. We will wrestle with uncertainty, diffused information, conflicting intuitions and multi-disciplinarity. Course graduates will be prepared to design their own made-to-order systems, and will be familiar with the lab techniques required to bring them to life. The course includes no laboratory component. It is ideally complemented by a wet lab rotation in molecular biology or participation to the iGEM competition.

Teachers: Gregory Batt (INRIA-Pasteur), Jakob Ruess (INRIA-Pasteur)

Objectives: Explaining how biological systems function based on their underlying biomolecular reactions (systems biology approach) and interfering with or even reprogramming these cellular functions (synthetic biology approach) are two major objectives of biological research.

Thanks to a long-lasting technological revolution, quantitative data are produced in increasing quality and quantity. Besides the qualitative interpretation of quantitative data, models are needed to make full use of the wealth of the available information.

So modeling approaches should help biologists to make a giant leap in their understanding on how biological systems work at the cellular level. Truth is that despite the huge potential, rational approaches have not yet delivered the expected results. Our capacity to predict the behavior of biological systems is surprizingly low in comparison to our prediction capacities for other complex systems such as aircrafts or computer networks. This is partly due to the fact that our "modeling technologies" are not efficient enough for this class of systems. But this is also largely the mere consequence of the fact that we do know yet what really matters to quantitatively explain the behavior of even simple cellular processes.

Our vision is that in a not-so-distant future, models and quantitative approaches will play a central role in biology, to assess our understanding in a principled manner and possibly also to orient further research. The age of "quantitative observation" should be followed by the one of "quantitative understanding". This course has the ambition to improve your readiness to these upcoming changes.

In concrete terms, our goal is to introduce basic principles for model development ("the art of modeling") and few fundamental mathematical and computational tools to analyze, assess and revise dynamical models of cellular processes. We will focus on modeling gene expression and genetic regulatory networks. We will employ elementary tools from dynamical systems theory for model analysis and from optimization methods for model calibration. Lastly, we will consider how biological variability can be represented by and analyzed using models.

Target audience: This course is primarily made for people not familiar with biomolecular process modelling, dynamical systems analysis, and computer programming. The sole requirements are elementary calculus and notions of molecular and cellular biology. Given the diversity of skills to acquire in a short time, a strong motivation to learn will be essential. We start from basal level but the slope is steep.

Syllabus:

• Modeling dynamical systems: system state, state space, variables, parameters constants, attractors, equilibrium, and stability
• Ordinary differential equation models for biochemical systems: mass action law, zero-, first-, and second-order kinetics, Michaelis Menten kinetics and quasi steady state approximations
• Modeling genetic networks in practice.
• Analysis of genetic network models in practice.
• Parameter search problems in systems biology: inverse problems and optimization problems, statistical viewpoints: frequentist vs Bayesian, notion of cost function, local vs global optimization
• Calibrating genetic network models in practice.
• Non-genetic variability in systems and synthetic biology: the different origins of noise, extrinsic variability vs intrinsic variability, stochastic models, analysis of stochastic models, calibration of stochastic models
• Writing, analyzing and calibrating stochastic biochemical models in practice.

Teachers: Nicolas Minc (IJM), Antoine Jégou (IJM), Paolo Pierobon (Curie), Jean-Léon Maitre (Curie)

Overview of the class:

The general aim of the course is to introduce students to the cross-talk between physical and biological mechanisms in the regulation of basic biological processes. The course will focus on physical mechanisms that underlie the regulation of large-scale organization at the cell- and tissue level, notably cell polarity, cell division, and morphogenesis. Emphasis will be put on the cytoskeleton, on mechanical forces, and on diffusion. Half of the course will be dedicated to introduce basics of the cytoskeleton, reaction-diffusion, and methods to study them, and the other half will focus on discussing examples in different molecular, cellular and tissue contexts.

Through the classes, students will learn about modern tools used in biophysics, such as quantitative imaging, force measurements and modelling, and their application to understand the spatial organization of a large range of molecular complexes, cell types and tissues.

Key questions that will be addressed include: How do cytoskeletal elements generate forces? How are these forces integrated by cells to position organelles or generate forces at the cell or tissue scale? How do they contribute to determine cell shape and size? How are these processes regulated in different organisms, at different scales in space and time?

Goal of the class: The course will provide students with a good knowledge of cytoskeleton regulation, and general biophysics. A number of classical experiments and techniques will be discussed. It will highlight differences between cell types, biological scales and conserved design principles or rules. Students will learn to observe, ask questions, formulate hypothesis and propose quantitative tests/experiments.

Syllabus:

• Actin and tubulin versatility: different ways to differentiate subunits (free monomers, in filaments, at ends, + nucleotide state).
• The role of diffusion for transport, reactions, and large-scale organization.
• Molecular motor properties, functions and modeling
• Prokaryotic cytoskeleton and other mechanisms for shaping bacteria.
• How cytoskeletal filaments are organized the way they are in cells.
• Basics of cell adhesion and force transmission.
• Cytoskeleton force generation, division positioning and cytokinesis.
• Orders of magnitude and scaling concepts of cytoskeleton. Mechanics and morphogenesis in cells and tissues
• Coarse-grained modelling

Teachers: Eugenio Cinquemani (INRIA), Vittorio Perduca (Université de Paris)

Course objectives:

The course aims at developing the students' critical thinking and ability to formalize a scientific question in a probabilistic framework. While providing a broad coverage of practical tools for statistical analysis, the objective is to bring students to a level of autonomy in seeking the right tools for the problems they will encounter in their career.

Overview of the class:

After an introductory discussion of the rationale of a probabilistic framework, we will briefly review the fundamental concepts of probability theory, and then develop and discuss commonly used methods for estimation and hypothesis testing (comparison of means, correlation analysis, regression, analysis of variance with parametric and non-parametric approaches). We will rely on rigorous but simple mathematical developments, putting emphasis on conceptual issues.

In pace with the teaching sessions, in the practical sessions we will apply the tools discussed to example problems including real-world data. Possibility of extra-modules on advanced topics.

Course syllabus:

• Basics of probability theory; Discrete and continuous probability distributions
• Mean and variance estimators; Estimation bias and error variance; Confidence intervals
• Role of sample size (consistency)
• Introduction to hypothesis testing; Type I-II errors, power and ROC; Parametric and nonparametric tests (Z test, T test ; Wilcoxon rank-sum test)
• Testing distributions: Kolmogorov-Smirnov and generalizations; ANOVA and Nonparametric ANOVA
• Correlation analysis; Parametric and nonparametric correlation tests (Pearson, Spearman); Linear regression
• Bayesian statistics: likelihood, conditional probabilities, examples of Bayesian inference

Teachers: Giuseppe Gangarossa (Université de Paris), Enrica Montalban (Université de Paris)

Overview of the class:

The goal of this course is to ensure that the students obtain broad training in the field of physiology and neuroscience. The course offers a rich experience that brings students to the forefront of research-based knowledge. Systems physiology and integrative neuroscience are intrinsically multi-disciplinary, spanning from molecular biology and gene regulation, to chemical and electrical signaling, and information processing. Each of these levels is combined to generate a mechanistic, molecular-to-systems level understanding of animal and human behaviours.

Students will integrate approaches from various science disciplines to formulate a more global understanding of complex and integrated phenomena. Introductory lectures cover the basics of physiology, endocrinology and neuroscience. Special lectures cover specific hot topics in the field of physiology and neuroscience.

Classes will be based on a hybrid system: frontal lectures, flipped classrooms and open discussions. A commitment to read articles and reviews is mandatory.

Course planning:

• 4 introductory lectures (3 hours each) to provide solid bases:

  1. Principles of physiology
  2. Principles of endocrinology
  3. Principles of neuroscience
  4. Cutting-edge tools in physiology and neuroscience

• 6 special lectures (3 hours each) on specific topics. Invited speakers for some topics.

  1. Learning and memory
  2. Neurobiology of the reward system
  3. Neurobiology of emotions
  4. Feeding behaviour, energy expenditure and homeostatic control
  5. Sensory neuroscience (smell, taste)
  6. Periphery-brain axis (microbiota, liver)

Teachers: Tamara Milosevic (Rhizome Association), Kristine Schauer (Curie)

Course objectives:

The general goal is to learn how to answer a scientific question in a team, through a quantitative experimental approach. The question has to be well formulated, the experiments well adapted to answer it and the result well interpreted (with its limitations).

By letting you, as much as possible, design the experiments, run them and interpret them, we hope that you will get ready for the long learning path of experimental sciences.

During the 2 weeks of project, you will learn not only how to perform these particular experiments, but also how to check the quality of the data, and to decide whether more experiments need to be done, from a first set of analysis. Extracted data will then be further analysed and interpreted, going back and forth between experiments and analysis until there are enough data to reach a conclusion. Each group will shortly present its results and discuss them in the mid-term session, before the final presentation taking place one week later. The goal of this last part is to judge whether the whole process led to an interesting answer or not, and to discuss about the next steps to take to go further if you were starting a longer term set of experiments.

Learning objectives:

• Find an agreement about an interesting science topic, using brainstorming techniques, active listening and through inclusion of opinions and ideas of each member of the team
• Examine and reference essential literature using Zotero
• State a clear hypothesis, which can be answered in a quantitative manner
• Apply time and project management tools to collaboratively conduct a research project
• Choose appropriate models, tools and methods to acquire quantitative data
• Construct a detailed budget of tools and materials needed for the execution of a full project
• Adapt the experimental setup based on the available time and resources
• Document all experimental efforts in a collaborative lab notebook
• Analyse quantitative data using descriptive statistics (and statistical tests?)
• Critically examine the results and assess what can or cannot be stated about your hypothesis
• Manage a constructive and inclusive working environment, in your team, and between teams
• Give and receive feedback, on science aspects and on skills
• Prepare visual, written and spoken presentations of a research project

Teacher: Jean-Christophe Thalabard (Université de Paris)

Overview of the course:

In the land of the monolingual: «Translating a basic finding into a new therapy requires us to speak many languages - scientific, clinical, legal and financial. Yet most of us are hopelessly monolingual, a limitation that substantially slows translational research. Steps have been taken to address this problem, but a lot remains to be done». Nature Medicine, 15, 975 (2009).

To achieve this goal, in addition to original articles, the major medical journals bring regularly to their readers updates on various aspects of basic research which could potentially be translated to humans. In addition research in humans raise specific issues, which are worth discussing per se. Articles will be selected in order to cover various aspects of clinical research, from early report of biotechnological and/or therapeutic advances, innovative designs to meta-analysis of published results when the time has come to globally evaluate previously promising approaches.

Course objectives: This excursion into major medical journals will help the students:

• to discover their contents, their target readership and how medically-oriented articles are structured and more importantly discussed;
• to summarize and present the results of both original and review articles in the medical field.

Teacher: Matteo Merzagora (TRACES)

Course description:

Communication skills are at the heart of scientific work. Communication is not a way to better «sell» research to funders, career enablers or the lay public. It is an intrinsic part of the research process itself: talking, listening, sharing, questioning... are communication activities which makes research possible. You don't learn science communication to communicate better, you learn science communication to do better research. This consideration is un underlying assumption of the whole course.

The first part of the course will be devoted to some training on how to talk to a scientific audience and to the lay public. Students will learn basic skills of science communication, how to structure a communication, the importance of identifying the key messages, etc. They will be evaluated based on a short presentation about their internship, given to their colleagues.

The second part of the course will explore the reverse of the communication process : how to listen to society at large for the benefit of research.

We will address the following question : how can a (future) scientist learn how to listen to the voices of art, culture, politics, society, etc. in order to give a deeper meaning to his.her research work ? What are the skills that need to be developed ? How can we improve our research skills by learning to understand and interpret a book, a film, a survey of public opinion, an advertising campaign, a politician’s speech, etc ? Students will develop independent work in pairs or small groups, based on their research interests and cultural interests. They will have to present their analysis, reflections, and possibly practical realisations to the whole group.

Learning objectives:

The class aims to address the following subjects:

• What is science communication? When and where do scientists communicate? How to interpret different audience's agendas? What is scientific culture ? Why is it interesting for science ? Why is it interesting for culture ?
• Definition of a science-culture project. Analysis of science-culture interactions. The case of cinema. The case of contemporary art.
• Preparing and delivering a presentation : tips and tricks
• The voice and the body: theatre techniques applied to science communication (intervention of a professional trainer)
• Science culture projects: review; mid term pitch; other exemples depending on student’s orientations
• Peer learning on scientific presentation (student's talk analyses in terms of communication qualities)
• Science culture projects - presentations, discussion
• Open topics on demand, based on TRACES training portfolio (exemples: studies of public perception of science, RRI and open science, science in cinema, careers in science communication, science museums and science exhibitions, science communication and social inclusion, etc.).

Teachers: Jérome Feret (ENS), Jean Krivine (IRIF), Pierre Boutillier (ENS)

Summary:

In this class, you will learn a new way, called rule-based modeling, to perform mechanistic modeling which is very different from that of the more usual approach through ODEs. We advocate the idea that a biological model should be considered correct when it has been provably obtained by integration of falsifiable data. In this context, we present an “executable knowledge representation” of biological mechanisms in the form of a graph rewriting language named Kappa. This approach builds models by writing rules that describe directly the possible interactions between proteins; these models can be equipped with rate laws and then simulated and analyzed with open source software tools (that we will provide). Intuitively, the syntax of Kappa is inspired by (bio)-chemistry and offers a transparent way to model, execute, and analyse, these interactions. The class is primarily practical where you will develop, think about and analyze a series of increasingly complicated systems using Kappa. There is also some pure lecturing time in order to explain the novel analysis tools offered by Kappa. The last part of the class is dedicated to physiological models of cells. As accurate as these models may be, their isolation from the physiological cellular context hampers the study of the role they can play in global cellular behaviors. A whole ​cell model is an aggregate of mathematical representations of cellular subprocesses (e.g. translation, protein maturation, etc.). These sub-models need to be validated against experimental data.

Objectives:

The main aim of the class is to help you to develop your intuitions about how signaling networks operate. The use of rule-based modeling makes it easy to try out variants of a model, which sometimes have very different behaviors, and so there is a strong emphasis on exploratory learning. You will also learn some specific technical material, notably about stochastic simulation, that complements what you have learned about ODE-based deterministic simulation in other classes.

In particular, we target systems that are difficult to model due to:

1. continuous update of the common knowledge about the interactions
2. the size of the systems and the high variabilities of the biochemical components that may occur in a run of a model
3. concurrency for common resources
4. highly separated scales of time and concentration
5. complex non-linear feedback control

Overview of the course:

• Big Mechanisms
• Gillespie Simulation
• DNA repair
• Static analysis
• Causal analysis
• Model reduction
• Model of growth

Teacher: Ariel Lindner (CRI)

Class objectives:

Students will be invited to investigate the various ways by which open science and citizen science serve research, learning and innovation for good, the revolution that it brings in the scientific organisation and how to maintain the research process open.

Learning objectives:

• Familiarise students with the open publication system
• Master and understand more deeply the steps of the research process
• Reflect on what is science and dispose of tools to open scientific processes
• Be prepared to extreme citizen science

M1 students will perform a long internship, 5 to 6 months, in France or abroad. This is their chance to apply what they learnt during their first semester intensive courses, to explore their passions, to gain precious lab experience and to learn how a research project is carried out in a real lab.

As part of the Master program, students attend monthly Masterclasses, which are special lessons given by invited speakers. The goal is to have our students interact with high-level scientists from all over the world, who come to share not only their science, but also an overview of their career, with positive and negative moments. It is a moment of open interaction and inspiration.

As an alternative to the long internship, you can apply to the iGEM Paris Bettencourt Team. Every year a small group of students from AIRE and other Masters programs around Paris gather their strengths and are hosted by the CRI to set up an iGEM project, and participate in this competition of synthetic biology. This usually starts with brainstorm sessions and project building, which does not require a full time involvement before May or June. Meanwhile, we expect that you find an internship of typically 3 to 4 months before joining the iGEM Team. Note that since the iGEM competition finale takes place in November, you will have to organize yourself to stay in the team up to that date. For those of you continuing with us in the second year of the Master, this means that at least part of your first lab rotation of M2 will be dedicated to finishing the iGEM team project.

Teacher: Stéphane Douady (CNRS - Université de Paris)

Overview: The workshop, set during a retreat in the Sologne region, intends to assemble free spirited students, and researchers from broad scientific backgrounds to conceive creative projects at the interface with Life, Learning and Digital Sciences.

The CIRP workshop attempts to provide the primary basis for collegiality and communication through dialogue and brainstorming on open questions in Life Sciences, Education Design, Entrepreneurship....

Aims of the workshop:

• To be able to focus on an important question and to define the means to approach it from different angles
• To be able to zoom out (have a broader view) and zoom in (be precise and define the key points)
• To think and express your ideas more clearly.
• To gain confidence in your ideas.
• To be able to discuss, reject or accept ideas.
• To learn to take constructive scientific criticisms
• To learn how to write a research proposal.
• To discuss questions thoroughly.
• To learn to interact with people from different backgrounds.

Teacher: Annemiek Cornelissen (CNRS - Université de Paris)

Overview:

This course is built of a series of seminars, each prepared by two students from different backgrounds, presenting in detail an interdisciplinary research paper of their choice. The underlying hypothesis, background and the results are discussed in detail and the different techniques explained.

In addition, the students are asked to integrate pros, cons and questions rose by the other students on the online course forum and suggest further experimental/modelling approaches with respect to their conclusions from the paper at stake.

All students participate weekly in the course forum, contributing their insights and questions on the article at hand.

Teacher: Danijela Vignjevic (Curie)

Overview: The course consists of a series of seminars, each initiated by two students from different backgrounds, presenting their review of scientific literature concerning a subject of their choice.

The research question, the motivation, scientific background and results are discussed in detail. In addition, students are required to tackle one emergent research question from their review by proposing a detailed method (experimental or theoretical/computational) to attempt to solve the question, and the motivation for the proposed method.

Course objective: Develop the students' ability to:

• find relevant and broad literature on a scientific subject of their choice
• delve into the background of said subject
• prepare a review in the form of a presentation aimed at an interdisciplinary audience.

Teachers: Manuel Théry (CEA), Stéphane Douady (CNRS - Université de Paris), Olivia du Roure (ESPCI), Danijela Vignjevic (Curie)

Overview: For the ZiZo course, you can choose among 3 different exercises:

• Grant writing: You will have a month to write a grant, then the groups that chose this exercise will review each others' grants and modify it accordingly.

• The book: You will choose to present a book, among a proposed selection of popular science books.

• Lab Tree: You will reconstruct and present the history of a chosen lab.

Teacher: Gabrielle Fausté

Course objectives

The goal of the project management course is to equip students with the required professional skills and tools to be able to manage their personal projects, learning and workload effectively. As a result of this course, they will get an understanding of the processes and activities of project management applied to individual work, hands-on experience in applying these theories in order to create a tailored project management system, as well as elements of effective collaboration.

Learning goals

• Students will be able to design a personal project management system to organize their personal, learning and project work: identify and list tasks, resources, dependencies, … Choose a set of tools (digital and analog) to track and organize their workload
• Objective setting, evaluation and reflection on completion and effectiveness
• Managing stakeholders and communications for complex projects
• Collaborating effectively in complex settings
• Developing skills of self-awareness, reflexivity
• Adopting a scientific approach to task and project management: setting goals, designing experiments (course of action), deploy, evaluate and learn, adjust
• Knowing the specificities of the main project management schools (agile, waterfall, ...) and how to choose the most relevant methodology depending on the tasks at hand

Competences developed

• Reflexivity and self-awareness
• Self-organization
• Self-efficacy
• Time and task management
• Effective collaboration
• Effective communication
• Future of work

This unit is a course of at least 4 ECTS of your own choice, which you take according to your career path. Do you want to learn more about a certain subject, or rather take some soft skills course? You can personalise your trajectory with the course that suits you best. You can either:

• Pick a course from the M1 list (if you joined directly in M2)
• Pick a course from another track of the AIRE Master
• Pick a course outside CRI
• Pick a course from the ones we offer (Entrepreneurship or Skills&Data).

This is the first of the two mandatory internships in our M2, and it must be performed in the Parisian area as it is mandatory to follow first semester courses at CRI. It is an internship of 4 or 5 months in the lab of your choice, and you will defend it with an oral presentation during a public event that you will organise with your M2 colleagues and with students from the FIRE doctoral school: the Thematic Workshops.

This is the second mandatory internship that you will have to perform in M2. It can be done abroad. It is an internship of 4 or 5 months in the lab of your choice, and you will defend it at the end of the year in late June - early July with a poster presentation.

As part of the Master program, students attend monthly Masterclasses, which are special lessons given by invited speakers. The goal is to have our students interact with high-level scientists from all over the world, who come to share not only their science, but also an overview of their career, with positive and negative moments. It is a moment of open interaction and inspiration.

Teacher: Stéphane Douady (CNRS - Université de Paris)

Overview: The workshop, set during a retreat in the Sologne region, intends to assemble free spirited students, and researchers from broad scientific backgrounds to conceive creative projects at the interface with Life, Learning and Digital Sciences.

The CIRP workshop attempts to provide the primary basis for collegiality and communication through dialogue and brainstorming on open questions in Life Sciences, Education Design, Entrepreneurship....

Aims of the workshop:

• To be able to focus on an important question and to define the means to approach it from different angles
• To be able to zoom out (have a broader view) and zoom in (be precise and define the key points)
• To think and express your ideas more clearly.
• To gain confidence in your ideas.
• To be able to discuss, reject or accept ideas.
• To learn to take constructive scientific criticisms
• To learn how to write a research proposal.
• To discuss questions thoroughly.
• To learn to interact with people from different backgrounds.

Teacher: Annemiek Cornelissen (CNRS - Université de Paris)

Overview:

This course is built of a series of seminars, each prepared by two students from different backgrounds, presenting in detail an interdisciplinary research paper of their choice. The underlying hypothesis, background and the results are discussed in detail and the different techniques explained.

In addition, the students are asked to integrate pros, cons and questions rose by the other students on the online course forum and suggest further experimental/modelling approaches with respect to their conclusions from the paper at stake.

All students participate weekly in the course forum, contributing their insights and questions on the article at hand.

Teacher: Danijela Vignjevic (Curie)

Overview: The course consists of a series of seminars, each initiated by two students from different backgrounds, presenting their review of scientific literature concerning a subject of their choice.

The research question, the motivation, scientific background and results are discussed in detail. In addition, students are required to tackle one emergent research question from their review by proposing a detailed method (experimental or theoretical/computational) to attempt to solve the question, and the motivation for the proposed method.

Course objective: Develop the students' ability to:

• find relevant and broad literature on a scientific subject of their choice
• delve into the background of said subject
• prepare a review in the form of a presentation aimed at an interdisciplinary audience.

Teachers: Manuel Théry (CEA), Stéphane Douady (CNRS - Université de Paris), Olivia du Roure (ESPCI), Danijela Vignjevic (Curie)

Overview: For the ZiZo course, you can choose among 3 different exercises:

• Grant writing: You will have a month to write a grant, then the groups that chose this exercise will review each others' grants and modify it accordingly.

• The book: You will choose to present a book, among a proposed selection of popular science books.

• Lab Tree: You will reconstruct and present the history of a chosen lab.

Teacher: Gabrielle Fausté

Course objectives

The goal of the project management course is to equip students with the required professional skills and tools to be able to manage their personal projects, learning and workload effectively. As a result of this course, they will get an understanding of the processes and activities of project management applied to individual work, hands-on experience in applying these theories in order to create a tailored project management system, as well as elements of effective collaboration.

Learning goals

• Students will be able to design a personal project management system to organize their personal, learning and project work: identify and list tasks, resources, dependencies, … Choose a set of tools (digital and analog) to track and organize their workload
• Objective setting, evaluation and reflection on completion and effectiveness
• Managing stakeholders and communications for complex projects
• Collaborating effectively in complex settings
• Developing skills of self-awareness, reflexivity
• Adopting a scientific approach to task and project management: setting goals, designing experiments (course of action), deploy, evaluate and learn, adjust
• Knowing the specificities of the main project management schools (agile, waterfall, ...) and how to choose the most relevant methodology depending on the tasks at hand

Competences developed

• Reflexivity and self-awareness
• Self-organization
• Self-efficacy
• Time and task management
• Effective collaboration
• Effective communication
• Future of work

This unit is a course of at least 4 ECTS of your own choice, which you take according to your career path. Do you want to learn more about a certain subject, or rather take some soft skills course? You can personalise your trajectory with the course that suits you best. You can either:

• Pick a course from the M1 list (if you joined directly in M2)
• Pick a course from another track of the AIRE Master
• Pick a course outside CRI
• Pick a course from the ones we offer (Entrepreneurship or Skills&Data).

This is the first of the two mandatory internships in our M2, and it must be performed in the Parisian area as it is mandatory to follow first semester courses at CRI. It is an internship of 4 or 5 months in the lab of your choice, and you will defend it with an oral presentation during a public event that you will organise with your M2 colleagues and with students from the FIRE doctoral school: the Thematic Workshops.

This is the second mandatory internship that you will have to perform in M2. It can be done abroad. It is an internship of 4 or 5 months in the lab of your choice, and you will defend it at the end of the year in late June - early July with a poster presentation.

As part of the Master program, students attend monthly Masterclasses, which are special lessons given by invited speakers. The goal is to have our students interact with high-level scientists from all over the world, who come to share not only their science, but also an overview of their career, with positive and negative moments. It is a moment of open interaction and inspiration.