ENS - Enseignement

Applications 2026-2027

Anne Zalmanski — 2025-12-18T09:32:00Z

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

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.

Climate Change Ecology — from Populations to Ecosystems

Alice Lebreton — 2024-03-02T16:00:56Z

Master in Life Science, ENS
UNBIO1-110 | CEPE - Climate Change Ecology — from Populations to Ecoystems
Level | Semester : M2 | S1
Where : Biology department, ENS, room 321
Duration : 1 week
Dates : September 14th-18th 2026
Maximum class size : 20 students

—2025-2026 program & syllabus—

Coordination

Primary instructor : Dr. Regis Ferriere (he/his), Biology department, ENS
Teaching Assistant : Elisa Richard (she/her)

Credits

3 ECTS

Keywords

Course prerequisites

Undergraduate level in population, community, and ecosystem ecology.
Students are expected to have received introductory training on the topics of population dynamics, species interactions, community diversity and stability, biogeography, ecosystem function and biogeochemical cycles.

Course objectives and description

Rapid changes to Earth's climate and biosphere influence how natural and managed ecosystems function and alter the services ecosystems provide. To address issues from conservation biology to sustainability, a thorough understanding of the responses and feedbacks of biodiversity and ecosystems to climate change is needed.
In this class, students will learn the basics of climate change ecology ; they will then be exposed to current topics and cutting-edge research, though a series of presentations and discussion with research experts.
Specific topics will address the physiological responses of organisms of multiple climate stressors ; the effects of climate acting in combination with other global changes ; integrative and multiscale approaches to document and predict ecological responses to climate change ; the societal challenges and opportunities of climate change ecology.

The course is intended primarily to M2 students in the IMaLiS Master program.
External students can attend and credit the class by prior arrangement with the primary instructor.

Please see contact information below. External students with attendance confirmed by primary instructor should register here at least one week before the start date of the class.

The class is taught in English.

Course Format and Teaching Methods
The course will include a combination of lectures by the primary instructor, hands-on activities (modeling, programming) with the co-instructor, and research presentations by guest speakers.
The course will take place in a classroom with in-house computer technology. However, students are strongly encouraged to bring their own laptop with needed software packages and libraries properly installed prior to class.

The objectives of the course are :

Expected Learning Outcomes
Upon completion of the course students will be able to :
• read, analyze, and present current research articles in Climate Change Ecology.
• connect climate and ecological processes.
• access and research ecological and climate data sets.
• develop quantitative models to formulate and evaluate hypotheses pertaining to the responses and feedbacks of ecological systems to climate change.
• study and relate ecological responses at different structural, temporal, and spatial scales.
• connect knowledge about ecological processes and function to conservation and sustainability challenges.

Assessment

There will be one homework assignment (25% of final grade) and one final assignment (75% of final grade).
The homework assignment consists in reading an assigned research paper and preparing a “reading write-up” by answering a set of questions designed to assess the understanding of the paper and its implications.
The final assignment consists in writing a mini-review on a prescribed topic. The mini-review will be five-page, single-spaced (references not included), due three weeks after the last day of the class.
There will be no re-take of the homework assignment or final assignment.

Absence and Class Participation Policies
Students are expected to be regular and punctual in class attendance and to fully participate in the course. Students themselves are primarily responsible for attendance and class participation.

Course material

Course material and announcements are posted on Moodle.
Specific instructions and resources will be provided regarding programming packages and libraries used for hands-on activities.
No special activities planned in this class.

Classroom Behavior Policy

To foster a positive learning environment, students and instructors have a shared responsibility. We want a safe, welcoming, and inclusive environment where all of us feel comfortable with each other and where we can challenge ourselves to succeed. To that end, our focus is on the tasks at hand and not on extraneous activities (e.g., chatting, texting, chatting, web surfing, etc.).

Subject to Change Notice

Information contained in the course syllabus may be subject to change with reasonable advance notice, as deemed appropriate by the primary instructor of this course.

QLife Quantitative biology winter school “Polygenic Adaptation : from Quantitative Genetics to Population Genomics ”

Alice Lebreton — 2024-03-02T16:00:54Z

Download here poster

Program

Download here tentative planning

Master in Life Science, ENS
BIO-Q-Qlife Winter School | Polygenic Adaptation : from Quantitative Genetics to Population Genomics
Year and Semester : M2 | S2
Where : Biology department, ENS
Duration : 1 week (March 10th -14th, 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 : Henrique Teotónio, Biology Department, ENS, France

Keywords

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, geoscience, physics, chemistry, computer science and mathematics. Knowledge or experience in the fields of experimental evolution or population genomics is recommended.

Course objectives and description

Aims and themes : Adaptation to novel environments depends on many alleles with small, but largely undetectable, fitness effects.
With the advance of DNA sequencing technologies, the combination of genome-wide association analyses with genome prediction methods has become the state-of-the-art approach to link adaptive trait responses to genetic changes at the molecular level.
The workshop will introduce students to evolutionary theory and the tools employed to test alternative models of polygenic adaptation. Current advances in detecting polygenic adaptation in experimental and natural populations will be discussed.
The course will introduce the participants to the analysis of phenomic and genomic data covering the latest software.

Organisation : Each day will include two introductory lectures in the morning, followed by computer tutorials in the afternoon (on some days the student can choose between two practicals). 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 8th, 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/1VySeNcY0Y.
In addition, provide a CV, a motivation letter and a supporting letter from a supervisor as a single pdf file with “Qlife Polygenic Adaptation Winter School 2025_LASTNAME” as subject header to Qlife.events chez psl.eu

Speakers and Instructors

Neda Barghi, Vienna
Nicholas Barton, Vienna
Timothée Flutre, Paris
Frédéric Guillaume, Helsinki
Susan Johnston, Edinburgh
François Mallard, Paris
Katrina McGuigan, Brisbane
Luisa Pallares, Tubingen
Patrick Phillips, Eugene
Christian Schlötterer, Vienna
Bertrand Servin, Toulouse
Erik Svansson, Lund
Jacqueline Sztepanacz, Toronto
Henrique Teotónio, Paris
Céline Teplitsky, Montpellier
Pierre de Villemereuil, Paris
Ben Wölfl, Vienna

ENS - Enseignement

Applications 2026-2027

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

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

Climate Change Ecology — from Populations to Ecosystems

Coordination

Credits

Keywords

Course prerequisites

Course objectives and description

The objectives of the course are :

Assessment

Course material

Suggested readings in relation with the module content

Classroom Behavior Policy

Subject to Change Notice

QLife Quantitative biology winter school “Polygenic Adaptation : from Quantitative Genetics to Population Genomics ”

Coordination

Keywords

Course prerequisites

Course objectives and description