ENS - Enseignement

Applications 2026-2027

Anne Zalmanski — 2025-12-18T09:32:00Z

Graduate Program Excellence in Life Sciences scholarships

Anne Zalmanski — 2025-12-04T14:22:41Z

A scholarship program offering competitive stipends (up to 10,000 €/year) for students following the Interdisciplinary Master in Life Science (IMaLiS) has been established by the Graduate Program in Life Sciences to specifically support international students.

Eligibility criteria for applying to a Graduate Program Excellence in Life Sciences scholarship in the Master M1 year :

– Students holding an international foreign Bachelor's degree in Life Sciences or in another scientific discipline, but with a demonstrated background in Life Sciences, are eligible to apply to the scholarship program at the Master 1 level.

– Candidates must not have lived in France during the academic year of the selection (September 1st – August 31st) nor the previous year.

Please note : Students admitted at the M1 level may obtain a one-year scholarship that can be renewed for one additional year to cover the second year of IMaLiS. Recipients of the scholarship will be required to undertake their internship in laboratories affiliated with PSL.

Application procedure

Application for a scholarship is part of the application to the IMaLiS Master's program (only one application is required).
You will need to complete the PSL online application form for the Master IMaLiS track. For required documents and evaluations steps, please the see application procedure website. The online application form will enable you to indicate whether or not you wish to apply to the Graduate Program Excellence in Life Sciences scholarship program.

If you have been admitted to IMaLiS or placed on the waiting list, you will proceed to a remote oral examination on a biology-related topic, which will allow the panel to establish the list of the beneficiaries of the scholarships.
For the oral examination, students will be required to critically read a scientific article, that will be assigned to them beforehand.

On the basis of the interviews and exam results, a list of students accepted with funding and a ranked waiting list will be established.
Students on the main list will be enrolled in the Master and benefit from the scholarship.

Those on the waiting lists for both Master and scholarship will be enrolled in the Master, if students accepted to the Master withdraw, based on their ranking. If students who have obtained scholarships also withdraw, their scholarships will be offered to those on the waiting list, based on their ranking.

Timetable for the 2026/2027 academic year

Medical and molecular genetics

Frédérique Godfroid — 2025-09-02T14:47:01Z

Master in Life Sciences, ENS
UNBIO1-087 | Medical and molecular genetics
Year and Semester : M2 | S1
Where : Biology department, ENS
Duration : 1 week
Dates : September 22-26, 2025

—2025-2026 programme to come—

Coordination

Olivier Collin, Biology department ENS

Credits

3 ECTS

Course objectives and description

Ce cours de génétique médicale a pour but de jeter les bases des mécanismes sous-jacents aux maladies génétiques les plus courantes.

l'exemple de la maladie génétique mono-factorielle la plus fréquente chez les caucasiens, la mucoviscidose, l'identification du seul gène en cause, le canal ionique CFTR, et des quelques 2000 allèles morbides, la course contre la montre depuis une trentaine d'années entre les travaux visant à comprendre la physiopathologie de cette maladie, grâce en particulier à la cryo-microscopie électronique, la modélisation en 3D de la structure de CFTR, et les différentes thérapies qui ont permis d'allonger de 20 ans l'espérance de vie des patients ;
les génétiques mono-factorielles de la surdité, mais avec différentes formes de surdité, et les difficultés pour identifier des familles informatives parce que les sourds se marient entre eux ;
la génétique poly-factorielle extrêmement complexe de l'autisme ;
la génétique poly-factorielle du sommeil, les aspects moléculaires des cycles circadiens et leurs régulations par les facteurs environnementaux ;
les génétiques poly-factorielles des différentes formes de diabète.

Pour chacun de ces syndromes, nous aborderons des questions techniques, mais aussi éthiques voire philosophiques sur les avancées récentes dans les traitements de ces maladies.

Qlife Quantitative Biology Winter School "Quantitative Approaches to DNA Damage and Repair"

Bofei Ma — 2025-06-30T08:47:09Z

Program

Download here tentative planning

Master in Life Science, ENS
BIO-Q-Qlife Winter School | Quantitative Approaches to DNA Damage and Repair
Year and Semester : M2 | S2
Where : Biology department, ENS
Duration : 1 week (March 23rd -27th, 2026)
Credits : 3 ECTS
Maximum class size : 25 students
This course is open to external students ->Contact

Coordination

Patrick Charnay, ENS Biology Department, France

Chairman of the scientific committee :
Terence Strick, ENS Biology Department, France

Course prerequisites

Basic experience in file manipulation under Unix/Linux and coding ability in Python or R. Attendance is competitive (25 participants) and open to M2 and PhD students, postdocs, engineers and junior scientists with backgrounds in chemistry, life science, physics, computer science and mathematics. Knowledge or experience in the fields of the school is recommended.

Course objectives and description

Aims and themes :
Recent technological developments in sequencing, imaging and image analysis have granted unprecedented access to the complex, dynamic, and sometimes even overlapping processes and pathways that nearly all organisms use to repair their DNA, thereby guaranteeing the integrity of their genome.
The Qlife program in Quantitative Biology of the PSL University organizes a 5-day winter school that will cover these emerging approaches through a series of lectures and digital workshops, using datasets from model organisms, both prokaryotic and eukaryotic. The dynamics of DNA repair processes will be explored using imaging approaches ranging from real-time single-molecule tracking of repair complexes to cellular-scale analysis. Quantitative analysis of the outcome of DNA repair pathways will be studied by overlaying sequence information with multiscale modelling of chromatin marks and contemporary understanding of the higher level physical organization of genomes into topologically-associated domains. These data will be integrated with the output of single-cell and spatial transcriptomic analyses to provide an unprecedented combined view of cell location, morphology, interactions, migration, expression pattern and fate.

Organisation

Each day will include two introductory lectures in the morning, followed by computer tutorials in the afternoon. The evenings will include keynote speaker seminars and poster presentations by the students.
Common lunches and dinners with the speakers and instructors will foster informal discussions.

Assessment of M2 students

After the course, students requiring a mark will write a written report on two of the computer tutorials, which will be assessed by the instructors.

Course material

The course will include introductory lectures, a series of hands-on computer tutorials run by experts in the field, seminars from prestigious researchers. In poster sessions, the students will have the opportunity to present their research and to obtain feedback from teachers.

Application Deadline

January 28th, 2026.

Registration fees

150 € (fees cover lunches from Monday to Friday and some dinners).

Application procedure

Register through this link https://forms.cloud.microsoft/e/h7Au5vMBmP.
In addition, provide a CV, a motivation letter and a supporting letter from a supervisor as a single pdf file with “Qlife DNA repair WS2026_LASTNAME” as subject header to qlife.events chez psl.eu

Speakers and Instructors

Dana BRANZEI, Essen
Chunlong CHEN, Paris
Nicola CROSETTO, Stockholm
Marie DOUMIC, Palaiseau
Marina ELEZ, Jouy-en-Josas
Paolo FAGHERAZZI, Brno
Fabio IANNELLI, Stockholm
Corinne GREY, Montpellier
Leonid MIRNY, Paris
Judith MINE-HATTAB, Paris
Raphaël MOURAD, Toulouse
Aurèle PIAZZA, Lyon
Hana POLASEK-SEDLACKOVA, Brno
Angela TADDEI, Paris
Martin TAYLOR, Edinburgh
Teresa TEIXEIRA, Paris
Terence STRICK, Paris

Qlife Quantitative Biology Winter School "AI-Accelerated Design and Optimisation of Compunds for Biological Applications"

Bofei Ma — 2025-06-30T07:47:22Z

Program

Download here tentative planning

Master in Life Science, ENS
BIO-Q-Qlife Winter School | AI-Accelerated Design and Optimisation of Compounds for Biological Applications
Year and Semester : M2 | S2
Where : Biology department, ENS
Duration : 1 week (February 9th -13th, 2026)
Credits : 3 ECTS
Maximum class size : 25 students
This course is open to external students ->Contact

Coordination

Patrick Charnay, ENS Biology Department, France

Chairman of the scientific committee :
Ilaria Ciofini, Chimie ParisTech PSL, France
Gilles Gasser, Chimie ParisTech PSL, France

Course prerequisites

Course objectives and description

Aims and themes : Recent technological developments in artificial intelligence (AI), machine learning and computational approaches have enabled in-silico design of compounds for medicinal and biological purposes with unprecedented speed and precision. The Qlife program in Quantitative Biology of the PSL University organizes a 5-day Winter School that will cover these cutting-edge approaches through a series of introductory lectures in the mornings, followed by digital workshops in the afternoons. Evenings will feature keynote speaker seminars and poster presentations by the students. The aim of this Winter School is to provide the attendees with a basic set of skills in different areas, including AI, TD-DFT, medicinal chemistry, photochemistry and chemical biology, with a clear emphasis on practical examples and guidance from experts in the field.

Organisation : Each day will include two introductory lectures in the morning, followed by computer tutorials in the afternoon. The evenings will include keynote speaker seminars and poster presentations by the students.
Common lunches and dinners with the speakers and instructors will foster informal discussions.

Assessment of M2 students

After the course, students requiring a mark will write a written report on two of the computer tutorials, which will be assessed by the instructors.

Course material

Application Deadline

January 4th, 2026

Registration fees

150 € (fees cover lunches from Monday to Friday and some dinners).

Application procedure

Register through this link
https://forms.cloud.microsoft/e/cmYTdzpVgD
In addition, provide a CV, a motivation letter and a supporting letter from a supervisor as a single pdf file with “Qlife AI-accelerated Design WS2026_LASTNAME” as subject header to qlife.events chez psl.eu

Speakers and Instructors

Davide Avagliano, Paris
Victor Batista, New Haven
Sophie Bombard, Orsay
Sylvestre Bonnet, Leiden
Ilaria Ciofini, Paris
Fernanda Duarte, Oxford
Angelo Frei, York
Gilles Gasser, Paris
Sherri McFarland, Arlington
Thijs Stuyver, Paris
Marta Vallejo, Edinburgh

Advanced Genetics

Anne Zalmanski — 2025-06-17T14:08:12Z

Master in Life Sciences, ENS – M1

2025-2026 - Semester 1

UNBIO1-122 - Advanced Genetics

6 ECTS

—2025-2026 program—

Year and Semester : M1 | S1
Duration : from September 19th 2025 to December 19th 2025
Hours : 2pm-5pm (Fridays)

1. Short Description of Course

This course explores the molecular mechanisms driving gene expression and genetic inheritance, with a focus on how genomic variation underlies the development of phenotypes.. Emphasis is placed on the interplay between genetic diversity and environmental factors in shaping expression patterns.
The curriculum delves into complex gene interactions, covering topics such as allelic series, epistasis, and metabolic dominance theory and it introduces the "genome-as-phenotype" concept, examining the roles of transposable elements, sex chromosome biology, and compensatory buffering mechanisms in shaping phenotypic outcomes.
Phenotypic variation is analyzed through quantitative frameworks to explain expressivity, penetrance, robustness, and canalization. The statistical genetics component emphasizes decomposition of phenotypic variance, heritability estimation, quantitative trait locus (QTL) mapping, and genome-wide association studies (GWAS) to uncover complex trait architecture and pleiotropic effects. The course will integrate concepts from population genetics and polygenic risk prediction, highlighting the role of phenotypic plasticity and environmental interactions in the genotype-phenotype relationship at both individual and population scales.

Maximum class size : 20 students.
The class is taught in English.

Keywords

Biology, life sciences, genetics, mutation, allelic series, dominance, epistasis, plasticity, epigenetics, TE, sex chromosomes, ploidy, expressivity, penetrance, robustness, canalization, heritability, animal model, QTL mapping, GWAS, pleiotropy, linkage disequilibrium, population structure, polygenic prediction, Human genetics

2. Registration

– Students external to the ENS Biology Department can attend and validate the class if the primary instructor has been contacted beforehand and agreed (see contact information below).
– Following approval, students need to register online at least one week before the course starting date.

3. Location and Timeline

Location : Biology Department, 3rd floor - at ENS, 46 rue d'Ulm, Paris.
Building entry with access card only (visitors must use the intercom at the entrance). The floor and class rooms are accessible without a badge. The building, floor and class room are generally accessible to people with disabilities.

Homework will consist in preparation of journal club discussion, slide presentations, and background reading.

4. Instructors and Contact Information

Primary instructors :
Gersende LEPERE
Henrique TEOTONIO
Preferred method of contact : email

5. Course Communications

Course materials (class syllabus, lecture slides, research articles, R scripts, etc.) will be made available on the Moodle platform.
Course announcements will be made by email and/or posted on Moodle.

6. Course Prerequisites or Co-requisites

Course prerequisites : students are required to have taken Molecular biology and genetics (L3), Math (L3), Biostats (L3).
Important concepts and skills to master : Mendelian genetics, linear regression, genome organization, DNA polymorphisms, mutations, meiosis, ploidy.
Level in programming : basic level in R.

7. Course Format, Teaching Methods, Special Activities

Course format and teaching methods : Lectures given by the primary instructors will be complemented with invited research seminars by external faculty, and student-led analysis and discussion of research articles.
At least one of the sessions will be a hands-on computer tutorial. Students are strongly encouraged to bring their own laptop with R studio installed prior to class.

8. Expected Learning Outcomes

Details to come.

9. Detailed Schedule and Content

There will be 13, on Friday 14h-17h, (see the general calendar for the dates, detailed schedule to be provided in the first class at the beginning of the course 19th September) :

1 Introduction (Mendelian Genetics)
2 Inverse Genetics (Mutation, promoter, enhancer, suppressor)
3 Gene Interactions (Allelic series)
4 Gene Interactions (Metabolic theory dominance, epistasis)
5 Plasticity and epigenetics
6 Expressivity and Penetrance (TD)
7 Expressivity and Penetrance (TD)
8 Genome as a phenotype (TE, Sex Chromosomes, Compensation)
9 QTL mapping and GWAS
10 Pleiotropy and linkage disequilibrium (TD)
11 Phenotypic variance decomposition (heritability, genomic prediction, polygenic score)
12 Genetic relatedness and the Animal Model (TD)
13 Human genetics

10. Evaluation and Grading

Students will be evaluated based on a written exam and small-group presentation of a research topic at the semester's end.

Student-led presentation 40%
Final exam 60%
Total 100%

11. Required or Suggested Resources

Recommended reading list (available in the science library and from the instructors) :
– Alberts, B., Heald, R., Johnson, A., Morgan, D., Raff, M., Roberts, K., & Walter, P. (2024). Molecular Biology of the Cell. W. W. Norton & Company
– Gibson, G., & Muse, S.V. (2004). A Primer of Genome Science. Sinauer Associates
– Griffiths, A.J.F., Wessler, S.R., Carroll, S.B., & Doebley, J. (2015) An Introduction to Genetic Analysis.
– W. H. Freeman. Kearsey, M.J., & Pooni, H.S. (1996). The Genetical Analysis of Quantitative Traits. Chapman & Hall
– Lynch, M., & Walsh, B. (1998). Genetics and Analysis of Quantitative Traits. Sinauer Associates
– Weir, B.S. (1996). Genetic Data Analysis II : Methods for Discrete Population Genetic Data. Sinauer Associates.

ABC-S : Understanding Biology through Structure

Anne Zalmanski — 2025-05-20T15:41:04Z

PSL Master in Life Sciences - ENS – M2

2025-2026 - Semester 1

UNBIO1-121 (PG-ABCS-S1) | ABC-S - Advanced Biology Course : Understanding Biology through Structure

3 ECTS

Poster-ABC_S-2025

—Download Planning—

Year : 1 (M1) / 2 (M2) and PhD
Semester : 1 (S1)
Duration : 12 sessions of 2 hours
Hours : From September 10th to December 10th on Wednesdays, 5:15-7:15 p.m.
Where : ENS Biology Department (46 rue d'Ulm, 75005 Paris)

Maximum class size : 24 students

Coordination
Anne Houdusse, Curie Institute
Antoine Taly, IBPC
Vincent Morin, IBENS
Bofei MA (Contact ENS for administration)

Credits : 3 ECTS

Keywords :
Molecules of life, Molecular interactions and structural cell biology, Physics and Chemistry of Life, Single molecule functional assays, Molecular dynamics and modelling, Allostery, Missense mutations and disease, Drug design, Alphafold and structure prediction by AI.

Course prerequisites :
The curriculum of the courses encompasses subjects such as fundamental biology. A description of the fundamental principles that allow acquiring function by the molecules of life will be given with principles in chemistry and physics as well as molecular biology. There is no specific prerequisite, as long as the student is sufficiently motivated to embrace broad subjects with interdisciplinary points of view.

Course objectives and description
Aims and themes :
Structural underpinnings are at the base of all molecular mechanisms that control the biological processes of life. The importance and power of combining exquisite molecular functional experiments and structural information has been continually demonstrated in the milestones that built knowledge in biology. The past two decades have seen a dramatic transformation take place in the field of structural biology. An integrative approach, the revolution in resolution of cryo-electron microscopy and cryo-electron tomography, the AI transformation for structure prediction and continuous advances in the depiction of macromolecular assemblies of RNA, DNA, proteins and lipids brings to scientists a treasure trove of insights. The course will demonstrate how structural and molecular dynamics studies can inspire testing new models with functional experiments and how dysfunction or deregulation that cause human pathologies can be better understood via structural studies. At last, the importance of structural approaches to accelerate the findings and development of future drug candidates will be presented in light of the AI revolution.

The lectures will revolve around seminars given by brilliant researchers, experts in different approaches of molecular biology. They are pioneers in new emerging topics and approaches at the frontier of science and are particularly keen to build their research together with other complementary disciplines of biology, physics and chemistry.

Organisation :
For each session, selected landmark papers will be shared with all students in advance. Two students will I) briefly present these key papers as an introduction to the seminar given by an expert and ii) will act as moderator of the discussion taking place after the presentation.

Assessment :
Validation for M1/M2 (with grades) : assiduity (presence to at least 80% of the sessions), article presentation + animation of class debate. Maximum 10-12 students.
– Validation for ENS diploma / Doctoral school (without grades) : assiduity (presence to at least 80% of the sessions), article presentation + animation of class debate. Maximum 10-12 students.
– Possibility to attend the course without validation in the limit of room availability

Course material (hand-outs, online presentation available, …) :
Slides and online presentations will be made available (with agreement of the speaker of each session)

Application procedure
Please send your application for registration, along with a short motivation letter and your CV, before the deadline of June 30th, 2025 to bofei.ma chez bio.ens.psl.eu.

Qlife Quantitative Biology Spring School "Cell Dynamics in Developmental Systems"

Anne Zalmanski — 2024-05-31T14:42:56Z

Download here poster

Download here tentative planning

Master in Life Science, ENS
BIO-Q-Qlife Spring School | Cell Dynamics in Developmental Systems
Year and Semester : M2 | S2
Where : Biology department, ENS
Duration : 1 week (March 31th –April 4th, 2025)
Credits : 3 ECTS
Maximum class size : 25 students
This course is open to external students ->Contact

Coordination

Patrick Charnay, Biology Department, ENS
Chairman of the scientific committee : Yohanns Bellaïche, Institut Curie, France

Keywords

Deep learning-based image analysis | mechanical forces | genetic networks | single cell transcriptomics | spatial transcriptomics

Course prerequisites

Basic experience in file manipulation under Unix/Linux and coding ability in Python or R. Attendance is competitive (25 participants) and open to M2 and PhD students, postdocs, engineers and junior scientists with backgrounds in life science, physics, chemistry, computer science and mathematics and a strong interest in Developmental Biology.

Course objectives and description

Aims and themes : Recent technological developments in sequencing, imaging and image analysis have granted access to unprecedented temporal and spatial resolution of gene expression, cell dynamics and morphological features.
The Qlife program in Quantitative Biology of the PSL University organizes a spring school that will cover these emerging approaches through a series of lectures and digital workshops, using datasets from Drosophila, ascidians and mammals. Dynamic, quantitative analysis of tissue development will be performed through the combination of image analysis (deep learning-based segmentation, cell tracking, registration) with multiscale analysis of forces and modeling. These data will be integrated with the output of single cell and spatial transcriptomic analyses to provide an unprecedented combined view of cell location, morphology, interactions, migration, expression pattern and fate.

Organisation : Each day will include two introductory lectures in the morning, followed by digital workshops in the afternoon (on most days, the student can choose between two workshops). The evenings will include keynote speaker seminars and poster presentations by the students.
Common lunches and dinners with the speakers and instructors will foster informal discussions.

Assessment of M2 students :

After the course, students requiring a mark will write a written report on two of the computer tutorials, which will be assessed by the instructors.

Course material

Application Deadline

January 19th, 2025

Registration fees

150 € (fees cover lunches from Monday to Friday and some dinners).

Application procedure

Register through this link https://forms.office.com/e/zmcfDKmqMt.
In addition, provide a CV, a motivation letter and a supporting letter from a supervisor as a single pdf file with “Qlife Cell Dynamics School 2025_LASTNAME” as subject header to Qlife.events chez psl.eu

Speakers and Instructors

Stein Aerts, Leuven
James Briscoe, London
Florence Cavalli, Paris
Kate Mc Dole, Cambridge UK
Alessandro De Simone, Geneva
Geneviève Dupont, Brussels
Emmanuel Faure, Montpellier
Lucie Gaspard-Boulinc, Paris
Edouard Hannezo, Klosterneuburg
Vincent Laville, Paris
Nathalie Lehmann, Paris
Patrick Lemaire, Montpellier
Adrien Leroy, Paris
Lorette Noiret, Paris
Jean-Yves Tinevez, Paris
Pavel Tomancak, Dresden/Brno
Hervé Turlier, Paris
Thierry Voet, Leuven

Members of the Scientific Committee

Yohanns Bellaiche
Jérôme Gros
Thomas Lecuit
Patrick Lemaire
Romain Levayer
Lorette Noiret
Iris Salecker
Denis Thieffry
Jean-Yves Tinevez
Hervé Turlier
Céline Vallot

Machine Learning in Python with scikit-learn

Anne Zalmanski — 2024-03-07T13:57:21Z

Graduated Program in Life Science, Department of Biology, ENS-PSL
BIO-AA-PG- | Machine Learning in Python with scikit-learn (ENS/Biology)
Level | Semester : PhD and Postdocs | S2
Where : Biology department, ENS
Duration : 4 weeks
Dates : May 12th – June 11th, 2026
May 12th and 13th ;
May 19th, 20th and 21st ;
June 2nd, 3rd and 4th ;
June 9th, 10th and 11th

Hours : 17:00-19:00, two or three times per week
Maximum class size : 16 students

Coordination

Prof. Denis Thieffry, Department of Biology, ENS

Instructors

Prof. Denis Thieffry, Department of Biology, ENS
Prof. Pedro Monteiro (NESC-ID/IST, Univ. Lisboa)

Credits

3 ECTS

Keywords

Python | Programming | Linux | Machine learning | scikit-learn

Course prerequisites

Basic Linux command and background in Python coding (including numpy arrays, pandas dataframes, making plots).
If you have no Linux/Unix background, you can check the first sections of an online course such as https://www.tutorialspoint.com/unix/index.htm

Course objectives and description

Aims

The objective of the course is to initiate young life-science scientists to the bases of machine learning, and how to use it in Python with the scikit-learn package.

Organization

The course will include eleven classes (two or three per week), each two-hours long, over a period of five weeks, in May-June 2026. A large part of each class will be devoted to practical coding exercises. A few hours of homework per week are further needed.

Assessment

• The participants will be regularly asked to explain their code during the classes.
• Coding exercises will be proposed over the duration of the course.
• The course will be assessed through attendence and solutions to exercices to be posted via the Moodle page of the course.

Course material

The course material will be shared via the Moodle of the Department of Biology of ENS.

Ecology for Global Health

Alice Lebreton — 2024-03-02T16:00:59Z

Master in Life Science, ENS – M2

2026-2027 - Semester 1

UNBIO1-109 (EfGH) - Ecology for Global Health

3 ECTS

—2025-2026 Provisional program—

Level | Semester : M2 | S1
Where : Biology department, ENS
Duration : 1 week
Dates : Novembert 30th-December 4th 2026

Maximum class size : 30 students

Coordination

Kévin JEAN, ENS-PSL

Credits

3 ECTS

Keywords

Infectious disease ecology| EcoHealth | One Health | Planetary Health

Course prerequisites

Introduction to Ecology (UNBIO1-103 or equivalent)
Some experience in data analysis with R

Course objectives and description

Aims

This course aims to present how considering ecological determinants and processes can contribute to the understanding and preservation of human and planetary health, especially in the era of the Anthropocene.
The course is primarily designed for students with a background in biology and ecology. It aims to present core concepts such as Global Health, One Health, and Planetary Health.

It will illustrate how ecological methods and approaches can be applied to address key issues affecting human health, especially :
– How biogeography and macro-ecology may help understanding the spatial distribution of infectious disease,
– How community ecology may help understanding the dynamics of pathogens and and evaluating disease control strategies,
– How community ecology may help understanding the future of infectious disease in the face of climate change,
– What are the fundamentals of epidemiology, which can be grasped as the application of ecology to human health to study both communicable and non-communicable diseases.

Organization

This is a one-week intensive course based on lecture-style presentations, including lectures by internationally recognized experts, and practical sessions. Practical sessions will require a basic knowledge on data analysis using the R statistical software.

Assesment

Module validation will be based on active participation during the week and on a group presentation and critical appraisal of a recent scientific study on a topic related to the module (Friday afternoon).

Register

The course is open to external Master and PhD students. To apply, please send a short CV and explain your motivation in an email to the coordinator no later than 3rd November.

ENS - Enseignement

Applications 2026-2027

Graduate Program Excellence in Life Sciences scholarships

Medical and molecular genetics

Coordination

Credits

Course objectives and description

Qlife Quantitative Biology Winter School "Quantitative Approaches to DNA Damage and Repair"

Coordination

Course prerequisites

Course objectives and description

Organisation

Assessment of M2 students

Course material

Application Deadline

Registration fees

Application procedure

Speakers and Instructors

Qlife Quantitative Biology Winter School "AI-Accelerated Design and Optimisation of Compunds for Biological Applications"

Coordination

Course prerequisites

Course objectives and description

Assessment of M2 students

Course material

Application Deadline

Registration fees

Application procedure

Speakers and Instructors

Advanced Genetics

1. Short Description of Course

Keywords

2. Registration

3. Location and Timeline

4. Instructors and Contact Information

5. Course Communications

6. Course Prerequisites or Co-requisites

7. Course Format, Teaching Methods, Special Activities

8. Expected Learning Outcomes

9. Detailed Schedule and Content

10. Evaluation and Grading

11. Required or Suggested Resources

ABC-S : Understanding Biology through Structure

Qlife Quantitative Biology Spring School "Cell Dynamics in Developmental Systems"

Coordination

Keywords

Course prerequisites

Course objectives and description

Assessment of M2 students :

Course material

Application Deadline

Registration fees

Application procedure

Speakers and Instructors

Members of the Scientific Committee

Suggested readings

Machine Learning in Python with scikit-learn

Coordination

Instructors

Credits

Keywords

Course prerequisites

Course objectives and description

Aims

Organization

Assessment

Course material

Ecology for Global Health

Coordination

Credits

Keywords

Course prerequisites

Course objectives and description

Aims

Organization

Assesment

Register

Suggested readings