16 parallel-computing-numerical-methods-"Multiple" PhD positions at Linköping University in Sweden
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Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Horizon 2020 Is the Job related to staff position within a Research Infrastructure? No Offer Description
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material, and produces high-quality documents. Furthermore, you have a solid understanding of numerical data and can solve numerical tasks quickly and easily. Experience in route optimization and strong
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2026 - 12:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within
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application! We are looking for a PhD student in Statistics with placement at the Division of Statistics and Machine Learning, Department of Computer and Information Science. Your work assignments As a PhD
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes
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issues in federated and decentralized learning systems. The aim is to develop novel methods for securing communication against passive and active adversaries, leveraging tools from statistical estimation
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26 Sep 2025 Job Information Organisation/Company Linköping University Research Field Computer science Researcher Profile First Stage Researcher (R1) Country Sweden Application Deadline 17 Oct 2025
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assignments Your tasks will be to carry out research using advanced theoretical and computational methods within quantum mechanics and statistical physics with the aim to study novel materials synthesized
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in both wet lab work and bioinformatics analysis of Oxford Nanopore long-read sequencing data related to X-linked diseases. Skilled in proteomic methods using MALDI-TOF and HPLC-MS, including data
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic