April 2026 - BBClist - maillist.psb.ugent.be

AI and computational biology conference - 9-10 December 2026 in Leuven
by BeNeLux bioinformaticians forum 30 Apr '26

30 Apr '26

Dear colleague, We’re pleased to invite you to the AI and computational biology conference which will take place on 9-10 December 2026 in Leuven, Belgium and is organized by VIB, a leading life sciences research institute in Flanders. 20 key scientists from academia and industry will present their latest insights in sessions focusing on the following topics: Genome to function Cell to system Disease modeling Innovation in machine learning If you want a complete overview of what’s happening now in these exciting fields, join your colleagues at #AIandCompBio26. Upcoming deadlines Travel grant deadline: 16 September 2026 Abstract deadline: 7 October 2026 https://www.vibconferences.be/events/ai-and-computational-biology Speaker line-up for AIandCompBio26 Here are the confirmed scientists who will showcase their latest breakthroughs: Mohammed AlQuraishi Columbia Systems Biology, US Valentina Boeva ETH Zurich, CH Vincent Dutordoir Google Deepmind, UK Jonas Fleck Roche Institute of Human Biology, CH Jan Funke Human Technopole, IT Pedro Gonçalves VIB Center for AI and Computational Biology & KU Leuven, BE Anna Kreshuk EMBL, DE Jakob Macke Max Planck Institute for Intelligent Systems, DE Bernardo Pereira de Almeida InstaDeep, FR Julia Reisenbauer Institute of Science and Technology Austria, AT Peter Robinson Berlin Institute of Health, DE & Jackson Laboratory, US Samuel Sledzieski Flatiron Institute Center for Computational Biology, US Andrea Sottoriva Human Technopole, IT Amos Tanay Weizmann Institute of Science, IL Sarah Teichmann University of Cambridge, UK Eric Xing Mohamed Bin Zayed University of Artificial Intelligence, AE Nir Yosef Weizmann Institute of Science, IL You can find the preliminary program on the conference website: Present your research via a selected talk or a poster We look forward to hearing about your research at this conference. You can submit your abstract for the poster sessions and the selected talk slots. Poster presenters will have a chance to win the AIandCompBio26 Poster Prize. The best abstracts will be given a selected talk slot in the program. The deadline for abstract submission is 7 October 2026. We offer travel grants to international junior scientists, which will reimburse travel costs up to 400 Euros. Are you interested in attending AIinCompBio26 in Leuven and want to have a chance to receive a travel grant? Then submit your motivation below by 16 September 2026 the latest. Submit your application We hope we have piqued your interest and look forward to talking to you in December. Kind regards, VIB Training & Conferences Organizing Committee: Stein Aerts VIB Center for AI & Computational Biology, BE Dmitry Kobak University of Tübingen, DE Valeriya Malysheva VIB-UAntwerp Center for Molecular Neurology, BE Yves Moreau KU Leuven, BE Joana Pereira VIB Center for AI & Computational Biology, BE Anastassia Vorobieva VIB-VUB Center for Structural Biology, BE; VIB.AI, BE Alexander Botzki VIB Training & Conferences, BE Lisa Thyrion VIB Training & Conferences, BE Disclaimer: This message and any attachments are intended solely for the named recipient(s) and may contain confidential, privileged, or protected information. Any unauthorized review, use, disclosure, or distribution is strictly prohibited. If you have received this message in error, please delete it and notify the sender immediately.

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Three bioimaging data analysis courses: Machine Learning techniques with Ilastik | Fiji | QuPath - May-June 2026
by BeNeLux bioinformaticians forum 30 Apr '26

30 Apr '26

Dear all, We are happy to announce that there are still some spots available for the upcoming Bioimaging-related courses in May and June 2026. The first course has machine learning focus using Ilastik<https://www.ilastik.org/>, followed by the QuPath essentials and the classical Fiji course. Teach your computer to see objects on bioimages with Ilastik 3 June 2026 | Leuven Registration deadline: 22 May 2026 What you will learn: * Understand the principles of supervised machine learning for image segmentation * Create pixel and object classifiers in Ilastik for microscopy data * Export probability maps and segmentations to Fiji for further analysis * Automate workflows using the Ilastik–Fiji integration for batch processing * Apply and adapt pre-trained models from the BioImage Model Zoo Register at https://training.vib.be/all-trainings/teach-your-computer-see-objects-bioim… -------------------------------------------------- Quantitative bioimage analysis in QuPath: essentials 11 June 2026 | Antwerp Registration deadline: 3 June 2026 What you will learn: * Navigate QuPath and manage image analysis projects efficiently * Perform cell segmentation and quantify structures in whole slide images * Classify tissues using pixel- and object-based approaches * Extract quantitative features for downstream analysis * Automate workflows using basic scripting and batch processing Register at https://training.vib.be/all-trainings/quantitative-bioimage-analysis-qupath… -------------------------------------------------- Basic image processing using Fiji 12 June 2026 | Antwerp Registration deadline: 5 June 2026 Learning outcomes: * Understand the Fiji interface and core image analysis tools * Apply filtering, thresholding, and segmentation techniques * Perform spatial and intensity measurements on biological images * Use key plugins for life science image analysis * Build and automate simple workflows using macros * Adapt scripts to fit specific experimental needs Register at https://training.vib.be/all-trainings/basic-image-processing-using-fiji-9 ————————————————————————— We are looking forward to seeing you at one of our upcoming sessions. Best regards, Alex Disclaimer: This message and any attachments are intended solely for the named recipient(s) and may contain confidential, privileged, or protected information. Any unauthorized review, use, disclosure, or distribution is strictly prohibited. If you have received this message in error, please delete it and notify the sender immediately.

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POSTDOCTORAL POSITION IN THE DEVELOPMENT OF MACHINE LEARNING and DEEP LEARNING METHODS GENETICS and BIOINFORMATICS
by BeNeLux bioinformaticians forum 29 Apr '26

29 Apr '26

*POSTDOCTORAL POSITION IN THE DEVELOPMENT OF MACHINE LEARNING and DEEP LEARNING METHODS GENETICS and BIOINFORMATICS* We are looking for a motivated postdoctoral researcher to join the _AI for Genome Interpretation (AI4GI_ <https://www.igmm.cnrs.fr/team/ia-pour-linterpretation-du-genome/>) group at the IGMM (CNRS, Montpellier) for *12 months*. The contract *can be renewed for extra 36 months* if the project passes the evaluation steps. *Are you a machine learning expert, proficient in programming with tensors and vectorial operations (pytorch, numpy)? Do you know the */*ins and outs*/*of machine learning methods and you can build neural networks from scratch? Do you enjoy developing new neural network architectures to solve non-conventional problems? This position might be for you!* We are looking for a *motivated* and curious candidate, with a *strong background in the development of machine learning methods for bioinformatics. * _*Context:*_**The position is based at the Institute of Molecular Genetics of Montpellier (IGMM, CNRS), in a highly international and interdisciplinary research environment. _Montpellier is a dynamic Mediterranean city_ <https://www.montpellier-france.com/> with an exceptional environment, culture and quality of life. It is home to numerous high-quality research institutes and the Montpellier University, a vibrant 70,000 student population and one of the world’s oldest medical schools. _*The Lab: *_The work will be carried out in the _AI for Genome Interpretation (AI4GI_ <https://www.igmm.cnrs.fr/team/ia-pour-linterpretation-du-genome/>) group, led by Dr. Daniele Raimondi. The group focuses on the development of advanced artificial intelligence and machine learning methods for genome interpretation, with a particular emphasis on modeling the relationship between genetic variation and phenotypic outcomes. AI4GI develops tailor-made neural network architectures, including sparse and biologically informed models, to predict disease risk and complex quantitative traits from large-scale genomic data such as whole-genome and exome sequencing. By combining methodological innovation in AI with applications in human genetics, cancer genomics, and plant genomics, AI4GI aims to advance our understanding of genotype–phenotype relationships, and precision medicine. _*The project:*_ This project aims at developing a new paradigm of General Genome Interpretation (GenGI) models by combining *DNA Large Language Models* (DLLMs) with *Deep Neural Networks* to predict human phenotypes directly from Whole Exome Sequencing samples from the *UKBiobank*. The project aims at the wide-spectrum prediction of human phenotypes, unlocking new frontiers in clinical genetics, precision medicine, disease risk prediction, and Explainable AI on genomics data. The candidate will: * Start by familiarizing with existing research and methods for genome interpretation * Familiarize with the sequencing data and its pre-processing * Study how DNA LLM work, and develop solutions to integrate them into the neural network architectures developed by the lab. * Focus on developing *low level *solutions for the scalability of neural networks and large language models to whole genome sequencing data * Develop *from scratch *algorithms and neural network architectures for the prediction of structured outputs (i.e. trees, graphs) * Implement and develop methods for the interpretation of neural network predictions and outputs, including concept-based activation and conterfactual analyses. The project focuses on the development of new neural network architectures to perform inference on sequencing data. *Candidate profile* Bioinformatics and genome interpretation are multidisciplinary and rapidly evolving fields. We are looking for a candidate who: * Has a background in computer science, mathematics, or physics, with a strong focus on machine learning * Is eager to continuously learn new skills, methods, and concepts * Enjoys tackling novel and unforeseen challenges with strong problem-solving skills *Required skills and expertise* * Strong background in neural networks, machine learning, linear algebra, and a working understanding of statistics * Deep understanding of machine learning foundations, including: o Linear algebra (vector and matrix operations) o Optimization methods o Neural networks (with practical experience in PyTorch) * Solid programming skills in Python and scientific computing (e.g., PyTorch, scikit-learn, NumPy) * Proficiency with GNU/Linux environments (including tools such as SSH) * Good communication and teamwork skills *Additional (preferred) qualifications* * Familiarity with GWAS, population genetics, or bioinformatics pipelines * Experience processing genomic data (e.g., whole-exome or whole-genome sequencing) * Basic understanding of genetics and biology *Other information* * The project involves developing unconventional neural network models using PyTorch * A minimum English level of B2 is required * Applications must be submitted in English *Practical details* * Location: IGMM, Montpellier * Duration: *12 months*. * Starting date: flexible, but the candidate must be selected *in the first half of 2026*. If you’re interested in working at the crossroads of AI, machine learning, bioinformatics and genomics - and in developing new methods rather than just applying existing ones - we’d like to hear from you. Applications should be made at this link: https://emploi.cnrs.fr/Offres/CDD/UMR5535-SARADE-107/Default.aspx

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PhD open position on Computational approaches for Neuromuscular Junction Organoids (Aix-Marseille University, autumn 2026)
by BeNeLux bioinformaticians forum 20 Apr '26

20 Apr '26

Dear colleagues, We would like to draw your attention to an open PhD position in our group at Marseille Medical Genetics. The project focuses on developing graph-based computational methods for the integration of multi-omics data from neuromuscular junction organoids, with applications to neuromuscular disease modeling. We are looking for candidates with a strong background in computational biology or mathematics, and an interest in biological modeling and network-based approaches. Starting date: autumn 2026. Review of applications begins immediately and will continue until the position is filled. Full description and application details: https://www.marseille-medical-genetics.org/a-baudot/phd-position/ Please feel free to forward this to any student who might be interested. Best regards, Galadriel Brière and Anaïs Baudot

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Course: Multi-omics and data sciences in complex diseases - register now!
by BeNeLux bioinformaticians forum 20 Apr '26

20 Apr '26

We are happy to inform you about our exciting five-day course: Multi-omics and data sciences in complex diseases Date: June 22-26, 2026. Venue: Randwijck campus, Maastricht University, The Netherlands. Target audience: PhD candidates, postdocs, and senior researchers from academia as well as industry. Organisers: Collaboration between Maastricht University and BioSB, the Netherlands Bioinformatics and Systems Biology research school. Course contents: The course will cover experimental technologies and integrative data analysis approaches for the study of complex phenotypes. We will address approaches to study genetic and environmental interactions and recent developments in NGS-based applications, integrative multi-omics data analysis using multivariate and machine learning approaches, as well as knowledge integration tools and methods to extract biologically meaningful information. Registration and more information: BioSB: https://www.dtls.nl/courses/multi-omics-and-data-sciences-in-complex-diseas… Register this week to still benefit from early bird discount (until 27 April 2026)! Further questions: Course organisers Dr. Lars Eijssen (l.eijssen(a)maastrichtuniversity.nl<mailto:l.eijssen@maastrichtuniversity.nl>) or Dr. Rachel Cavill (rachel.cavill(a)maastrichtuniversity.nl<mailto:rachel.cavill@maastrichtuniversity.nl>) _________________________ Lars M.T. Eijssen Assistant professor Dept. of Translational Genomics Dept. of Psychiatry and Neuropsychology Maastricht University

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Save the date: Disease Maps Community Meeting, October 5-7, 2026, Rostock, Germany
by BeNeLux bioinformaticians forum 08 Apr '26

08 Apr '26

[Posted on multiple channels, apologies for potential duplicates] Dear all, We are pleased to announce the upcoming Disease Maps Community Meeting 2026, which marks an important milestone as the 10th community meeting since the first event in Lyon in 2017. The meeting will focus on updates from Disease Map projects, recent advances in systems biology modelling, the use of AI methods for model curation and exploration, and the translation of computational models into clinical practice. Details * When: October 5 – 7, 2026 * Where: Rostock, Germany * Registration and abstract submission: will be available soon on the event website * Registration and abstract submission deadline: August 31, 2026 * Travel: Rostock can be reached by direct train from Hamburg or Berlin, both of which have major international airports More information is available on the event website: https://disease-maps.io/DMCM2026/ Should you require any further information or assistance, please do not hesitate to contact us. Kind regards, on behalf of the organizers Matti van Welzen (né Hoch) Dept. of Systems Biology & Bioinformatics University of Rostock 18051 Rostock, Germany www.sbi.uni-rostock.de<http://www.sbi.uni-rostock.de/>

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⏰ ISMB 2026 CompMS – Abstract submission deadline (April 9, 2026)
by BeNeLux bioinformaticians forum 07 Apr '26

07 Apr '26

— ISMB 2026 CompMS – Abstract submission deadline (April 9, 2026) — [cid:f61875a4-4526-463b-b244-58a68a357050] We would like to remind you that the abstract submission deadline for the Computational Mass Spectrometry (CompMS) session at the ISMB 2026 conference is April 9, 2026. We encourage you to submit your abstract today and join us during the ISMB 2026 conference in Washington, DC (or virtually) on July 12–16, 2026. Key dates April 9, 2026: Abstract submission deadline May 5, 2026: Talk/poster acceptance notifications May 7, 2026: Late poster submission deadline May 14, 2026: Late poster acceptance notifications July 12–16, 2026: ISMB conference * July 13, 2026: CompMS COSI * Venue: Washington Hilton, 1919 Connecticut Ave NW, Washington, DC 20009, USA * Website: https://www.iscb.org/ismb2026 Abstract submission deadline The abstract submission deadline for ISMB 2026 is fast approaching! Submit your abstract to ISMB to present your work at the leading bioinformatics/computational biology conference. Attend the CompMS session to learn about the latest algorithmic advances in computational mass spectrometry. Please remember to select the CompMS COSI as your session of interest upon submitting your abstract. Call for abstracts: https://www.iscb.org/ismb2026/call-for-submissions/abstracts We look forward to seeing you at ISMB! The CompMS organizing committee. Wout Bittremieux Isabell Bludau Marie Brunet Lindsay Pino Ali Rahnavard Timo Sachsenberg More information about ISMB 2026: The Intelligent Systems for Molecular Biology (ISMB) is the world’s largest bioinformatics/computational biology conference. Every year it brings together scientists from computer science, molecular biology, mathematics, statistics, and related fields and provides an intense multidisciplinary forum for disseminating the latest developments in bioinformatics/computational biology. The conference fosters fresh dialogues, collaboration and learning opportunities, and is a gathering which shapes the future of the field. At the heart of the scientific program are ISCB’s Communities of Special Interest (COSIs), enabling community involvement and bolstering ISMB’s reputation as the leading conference in the field. The CompMS COSI promotes the efficient, high-quality analysis of mass spectrometry data through dissemination and training in existing approaches and discussion of new, innovative approaches. The CompMS initiative aims to exploit synergies between different mass spectrometry-based application domains, in particular proteomics, metabolomics, and lipidomics.

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