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Integrative Scalable Computing Laboratory

A research group at the Department of Information Technology, Uppsala Universtity.

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PhD student in Scientific Computing focusing on Secure Federated Machine Learning

Posted on May 11, 2022May 11, 2022 By Salman Toor No Comments on PhD student in Scientific Computing focusing on Secure Federated Machine Learning
PhD student in Scientific Computing focusing on Secure Federated Machine Learning

Project Description Artificial intelligence (AI) is at the core of modern-day applications. With the advent of massive datasets, the last two decades were dedicated to improve the mathematical modeling and training processes; And recently the focus has shifted towards security, privacy and trust based AI assisted solutions. Together with a number of other viable solutions,…

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Data Science, Data-Intensive Computing, Federated Learning, FedML, News, Open Positions

Open PhD position in Scientific Computing

Posted on May 3, 2022May 3, 2022 By Salman Toor No Comments on Open PhD position in Scientific Computing
Open PhD position in Scientific Computing

We have one open PhD position focusing on Cybersecurity and Machine Learning for Critical Infrastructures Application submission deadline: May 16, 2022 The application submission link is available on the following page: https://www.uu.se/en/about-uu/join-us/details/?positionId=501061 This PhD position is part of the eSSENCE – SciLifeLab graduate school in data-intensive science. The school addresses the challenge of data-intensive science both from…

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Applied Cloud Computing, Data Science, Data-Intensive Computing, News, Open Positions

Two Open PhD Positions

Posted on March 4, 2022April 2, 2022 By Prashant Singh No Comments on Two Open PhD Positions
Two Open PhD Positions

We welcome applications for 2 PhD positions in the group. This is an exciting opportunity to join us at SciLifeLab and the Division of Scientific Computing, UU to conduct highly interdisciplinary research in machine learning, computational science and systems biology. Please refer to the detailed advertisements below. Statistical Sampling/Active Learning for Large-Scale Scientific Experiments Machine…

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Data Science, News, Open Positions, systems biology

MSc thesis opportunities in privacy-preserving Machine Learning

Posted on November 10, 2019November 10, 2019 By admin
MSc thesis opportunities in privacy-preserving Machine Learning

We have opportunities for a number of MSc thesis students to work with the group in the spring semester 2020. Artificial intelligence is rapidly transforming our society. Machine learning models will be in every digital system we use, and it is imperative that we protect the integrity of data owners. In this project we work…

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Applied Cloud Computing, FedML, News, Open Positions

Postdoc in Scientific Computing/Applied Cloud Computing

Posted on July 1, 2016July 1, 2016 By admin No Comments on Postdoc in Scientific Computing/Applied Cloud Computing

We are looking for a talented individual to join our efforts on creating smart and scalable cloud services to support simulation-driven scientific discovery via large-scale computational experiments such as parameter sweeps. This is a classic and very important problem that we will approach in new ways, leveraging recent advances in cloud computing, data-intensive computing and machine…

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Applied Cloud Computing, Data Science, Data-Intensive Computing, News, Open Positions

Open Posititions: up to two PhD students

Posted on January 19, 2016March 14, 2016 By admin No Comments on Open Posititions: up to two PhD students

(Call for applications is closed. ) We are expanding the group with up to two PhD students in the areas of Applied Mathematics and Applied Cloud Computing: CIM, the Center for Interdisciplinary Mathematics are hiring students.  We are, in collaboration with the Spjuth lab offering the project, Smart and Efficient Scientific Software for Exploration of Vast Amounts…

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Applied Cloud Computing, Data Science, Data-Intensive Computing, Open Positions, Software, StochSS

Data-and simulation-driven life science. Much of our work in eScience and applied ML has applications in life science, and in Systems Biology in particular. We aim to enable data-and simulation-driven scientific discovery.

HASTE - a cloud native framework for intelligent processing of image streams: http://haste.research.it.uu.se/

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Andreas HellanderFollow

Andreas Hellander
A_HellanderAndreas Hellander@A_Hellander·
11 May

Are you using StochSS? Please help us gather insights into what is working well and what can be improved by filling in this short survey https://forms.gle/mEqfASuUd3MDWuPS9

@LindaPetzold @briandrawert @mhucka

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A_HellanderAndreas Hellander@A_Hellander·
9 May

Apply to this PhD student position in the eSSENCE and SciLifeLab graduate school in data-intensive science!

This project is the intersection of cybersecurity and big data with main supervisor @sztoor.
https://www.uu.se/en/about-uu/join-us/details/?positionId=501061

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A_HellanderAndreas Hellander@A_Hellander·
28 Apr

PhD position in the eSSENCE/@scilifelab graduate school in data-intensive science with @cnettel: https://uu.se/en/about-uu/join-us/details/?positionId=501716 Apply and be part of a new interdiciplinary research effort @UU_University!

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A_HellanderAndreas Hellander@A_Hellander·
23 Apr

If you are a current user of StochSS please let us know your thoughts by filling out this brief user survey: https://forms.gle/3r836iph8gqFEpZX7

#systemsbiology #stochss @LindaPetzold @briandrawert @prashant_rsingh

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Retweet on TwitterAndreas Hellander Retweeted
AssistSweASSIST Sweden@AssistSwe·
14 Apr

Soon the partners in the ASSIST project will attend a workshop on federated learning arranged by Scaleout. Partners from different countries (Sweden, Belgium, Netherlands, Turkey) will contribute with nodes that train a segmentation network.

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Decentralized AI, Federated Learning. One focus area of the group is development of methods and software to address decentralized and privacy-preserving AI. We are core contributors to the FEDn open source framework for scalable federated machine learning:

https://github.com/scaleoutsystems/fedn
Introduction to Federated Learning by Andreas Hellander
Join the discussion on Decentralized AI:

Scaleout Systems is a spin-out from ISCL on a mission to enable decentralized AI and federated learning to production.

https://www.scaleoutsystems.com/

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