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Machine learning and deep learning fundamentals
1 - 2 April 2026
Zwijnaarde, Belgium
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Artificial Inteligence programming software -
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Spring School - Interpretable Machine Learning Models in Biomedicine
2 - 6 March 2026
Altheim, Germany
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Microscopy data analysis: machine learning and the BioImage Archive
16 - 20 March 2026
Online
Machine learning Bioimaging Image analysis Bioimage analysis Machine learning models Scientific computing Light microscopy Electron microscopy -
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Introduction to Machine Learning with Python
1 - 22 June 2026
Online
data mining machine learning training torsten schwede & thierry sengstag group mark ibberson group -
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Introduction to Machine Learning with Python
1 - 2 October 2026
Bern, Switzerland
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data mining machine learning training torsten schwede & thierry sengstag group mark ibberson group -
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Introduction to Machine Learning with R
12 - 13 November 2026
Basel, Switzerland
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Statistics and Machine Learning for Life Sciences
31 March - 1 April 2026
Online
training biostatistics data mining machine learning torsten schwede & thierry sengstag group -
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Data-driven approaches to understanding dementia
13 - 17 April 2026
Online
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Systems biology: from large datasets to biological insight
11 - 15 May 2026
United Kingdom
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Systems biology Network analysis Machine learning Deep learning Network inference Logic modelling Multi-Omics Factor Analysis Data integration -
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Ensuring More Accurate, Generalisable, and Interpretable Machine Learning Models for Bioinformatics
17 November 2026 @ 09:00 - 17:00
Online
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CIBB 2026 – Computational Intelligence Methods for Bioinformatics and Biostatistics
2 - 4 September 2026
Rome, Italy
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Bioinformatics Computational biology Machine learning Data architecture, analysis and design Statistics and probability Medical informatics bioinformatics Biostatistics computational intelligence Artificial Intelligence Machine Learning data science computational biology medical informatics life sciences -
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Data science for life scientists
15 - 19 June 2026
United Kingdom
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Data science Python Data visualisation Statistics Machine learning
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Machine learning Statistics and probability Statistics
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Clustering in Machine Learning
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Age prediction using machine learning
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Machine learning: classification and regression
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Machine learning Statistics and probability Statistics
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Bioinformatics, Computational Biology, Computer Science, Programming, Coding, Education, Data Science, Transcriptomics, Machine Learning
R for Data Science: November 2024
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exercise, slides, tutorial
Machine Learning
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proteomicsML
ProteomicsML provides ready-made datasets for machine learning models accompanied by tutorials on how to work with even the most complex data types in the field of proteomics. The resource is set up to evolve together with the field, and we welcome everyone to contribute to the project by adding...
1 training materialproteomicsML https://proteomicsml.org/ https://tess.elixir-europe.org/content_providers/proteomicsml ProteomicsML provides ready-made datasets for machine learning models accompanied by tutorials on how to work with even the most complex data types in the field of proteomics. The resource is set up to evolve together with the field, and we welcome everyone to contribute to the project by adding new datasets and accompanying notebooks. ProteomicsML was set up as a joint effort of SDU, CompOmics, LUMC, PeptideAtlas, NIST, PRIDE, and MSAID. We believe that ProteomicsML is solid step forward for the field towards more open and reproducible science! /system/content_providers/images/000/000/676/original/proteomicsml-logo.png?1686658675 -
Pattern Institute
Mission | The Pattern Institute is a nonprofit research organization dedicated to advancing scientific discovery, education, and outreach, with a particular emphasis on systems and complexity science. It applies mathematical and computational approaches to uncover patterns across the...
3 training materialsPattern Institute https://www.pattern.institute/training/ https://tess.elixir-europe.org/content_providers/pattern-institute **Mission** | The **Pattern Institute** is a nonprofit research organization dedicated to advancing scientific discovery, education, and outreach, with a particular emphasis on systems and complexity science. It applies mathematical and computational approaches to uncover patterns across the natural, formal, and social sciences. /system/content_providers/images/000/000/822/original/pi-logotype2.svg?1753360127 -
EOSC4Cancer
EOSC4Cancer will make diverse types of cancer data accessible: genomics, imaging, medical, clinical, environmental and socio-economic. It will use and enhance federated and interoperable systems for securely identifying, sharing, processing and reusing FAIR data across borders and offer them via...
1 training material0 events (1 past event)EOSC4Cancer https://eosc4cancer.eu/ https://tess.elixir-europe.org/content_providers/eosc4cancer EOSC4Cancer will make diverse types of cancer data accessible: genomics, imaging, medical, clinical, environmental and socio-economic. It will use and enhance federated and interoperable systems for securely identifying, sharing, processing and reusing FAIR data across borders and offer them via community-driven analysis environments. EOSC4Cancer’s well curated data sets will be essential input for reproducible and robust analytics and computational methods – including machine learning and artificial intelligence. EOSC4Cancer’s five use cases will cover the patient journey from cancer prevention over diagnosis to treatment, laying the foundation of data trajectories and workflows for future European Cancer Mission projects. /system/content_providers/images/000/000/747/original/Logo-eosc-cancer-RGB-horizontal-STANDARD.png?1711439233