March 2022 - Infovis - infovis.org

BioVis Meetup #2: Visualisation of Spatial and Image Data, 22-Mar-2022-17:00 CET
by Helena Jambor 07 Mar '22

07 Mar '22

Invitation to the March ‘22 BioVis meetup: Visualizing biological localizations - Spatial data in single cell & bioimage datasets. — Speaking: Fabian Theis Squidpy - Spatial Single Cell Analysis and Visualisation. Fabian Theis is head of the Computational Health Center at Helmholtz Munich and the director of HelmholtzAI and Associate Faculty at the Wellcome Trust Sanger Institute. He uses artificial intelligence to unlock the secrets of human cells. He uses single cell sequencing and spatial transcriptomics data to study how do cells interact and what goes wrong with diseases at the cellular level. Heba Sailem: Visualisation of multiplexed and bioimaging data using ShapoGraphy. Heba Sailem is Sir Henry Wellcome Research Fellow at the Institute of Biomedical Engineering at the University of Oxford. She pioneered the development and application of several computational approaches to interrogate complex imaging data by artificial intelligence and multi-omics data integration. Using these approaches, she studies how changes in tissue architecture modulate cell signalling and contribute to diseases. — Details: BioVis meetup Location: https://tu-dresden.zoom.us/j/86078643977?pwd=dFZiNEIzcWhNUVRDZmt1MVdpWFpjUT… TUE, Mar 22nd [5pm CET, 4pm UK, 12am NY, 9AM SF] http://biovis.net — Why: The BioVis meetup is a new virtual seminar series organised by the BioVis network (http://biovis.net/) to complement the BioVis conferences at ISMB (July) and IEEE Vis (October). Why? We wanted to hang out more regularly with the BioVis community, with wet lab researchers, clinicians, bioinformaticians, visualisation researchers, designers, data scientists, all invested in biomedical data visualisation. Updatesa are posted on http://biovis.net/2022/meetup/ and mailing lists. Sign up to BioVis-Meetup(a)groups.tu-dresden.de<mailto:BioVis-Meetup@groups.tu-dresden.de> (email subject 'subscribe' to BioVis-Meetup-request(a)groups.tu-dresden.de<mailto:BioVis-Meetup-request@groups.tu-dresden.de>) — Best wishes, Helena Jambor and Heba Sailem ______________________________ Dr Helena JAMBOR MSNZ, NCT-UCC, MK1 Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden Fetscherstraße 74, 01307 Dresden Tel +49 (0)351 458 - 11780 Email helena.jambor(a)tu-dresden.de<mailto:helena.jambor@tu-dresden.de> Twitter @helenajambor

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ESANN 2022 call for papers
by Michel Verleysen 05 Mar '22

05 Mar '22

ESANN 2022 - 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Bruges, Belgium, 5-6-7 October 2022 https://www.esann.org Call for papers The call for papers is available at https://www.esann.org. Deadline for submissions: May 9, 2022. The ESANN conference addresses machine learning, artificial neural networks, statistical information processing and computational intelligence. Mathematical foundations, algorithms and tools, and applications are covered. ESANN 2022 builds upon a successful series of conferences organized each year since 1993. ESANN has become a major scientific event in the machine learning, computational intelligence and artificial neural networks fields over the years. The conference will be organized in hybrid mode, with both both in-person and online participation, including for speakers. The physical conference will be organized in Bruges, one of the most beautiful medieval towns in Europe. Designated as the "Venice of the North", the city has preserved all the charms of the medieval heritage. Its centre, which is inscribed on the Unesco World Heritage list, is in itself a real open air museum. We hope to receive your submission to ESANN 2022 and to see you in Bruges or online! ======================================================== ESANN - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning http://www.esann.org/ * For submissions of papers, reviews, registrations: Michel Verleysen UCLouvain - Machine Learning Group 3, pl. du Levant - B-1348 Louvain-la-Neuve - Belgium tel: +32 10 47 25 51 - fax: + 32 10 47 25 98 mailto:esann@uclouvain.be * Conference secretariat d-side conference services 24 av. L. Mommaerts - B-1140 Evere - Belgium tel: + 32 2 730 06 11 - fax: + 32 2 730 06 00 mailto:esann@uclouvain.be ========================================================

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Data Scientist Position
by Sohaib Ghani 01 Mar '22

01 Mar '22

Data Scientist Position The KAUST Visualization Core Lab (KVL) is seeking a highly motivated and collaborative data scientist with a strong background in machine learning and deep learning application design and support. KVL along with the Kaust Supercomputing Core Lab (KSL) advances the KAUST mission by providing cutting-edge visualization, HPC, and data science services; collaborating with domain researchers to accelerate discoveries through large-data analysis and visualization, machine learning, and data science; and supporting the needs of KAUST and In-Kingdom entities by providing access to and training on state-of-the-art visualization/HPC hardware and software for scientific discovery. The scientist will work in collaboration with other team members to build cutting-edge machine learning and deep learning workflows for domain scientists and industry partners on a variety of platforms, including Shaheen (KAUST's Cray XC40 supercomputer) and Ibex (KAUST's NVIDIA GPU Cluster). Major Responsibilities: • Assist KAUST stakeholders and their in-Kingdom partners in applying machine learning and deep learning tools and methods in their scientific research. • Survey relevant work from the HPC and data science communities to identify standard practices in optimizing machine learning and deep learning workflows for HPC machines. • Provide expert consulting on machine learning and deep learning methods as needed by KAUST stakeholders and their In-Kingdom partners. • Develop machine learning and deep learning workflows to analyze data collected by KAUST facilities and systems. • Provide hands-on data science and machine learning training to KAUST and In-Kingdom students/researchers. Competencies: • Proficiency in machine learning, deep learning, and data analytics. • Experience working with machine learning and deep learning frameworks such as Scikit-Learn, PyTorch, Tensorflow, etc. • Experience using tools to support self-service software installation and workflow management such as Git, Conda (+Pip), Docker, and Snakemake. • Experience developing and maintaining high-quality software documentation and conducting training and outreach activities. • Experience deploying machine learning and deep learning applications at scale. • Experience working with data generated by High-Performance Computing (HPC) machines. • Excellent communication and interpersonal skills. • Demonstrated ability to work effectively as part of a cross-disciplinary team. Qualifications: • Ph.D. degree in Computer Science or related field with demonstrated relevant expertise. Apply Here: https://bit.ly/3sujEIU Thank You Regards Sohaib --------------------------------------------------------------------------- Sohaib Ghani, Ph.D. Lead Visualization Scientist, https://corelabs.kaust.edu.sa/visualization/, King Abdullah University of Science and Technology, Thuwal, 23955--‐6900, Saudi Arabia.

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