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doctoral network on quantum error correction, as a PhD candidate at TU/e, designing next-generation codes and decoders for real quantum hardware. Information Quantum computers have grown remarkably fast
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
scholarships and some postdoc positions. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out research of good quality within the framework described above Apply
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The International Institute of Molecular Mechanisms and Machines Polish Academy of Sciences | Poland | 28 days ago
after the probation period. - Remuneration/month: Salary range - PLN 4,800–5,500 net/month. - The position can start on the 1st of October 2026. - Work in an active team in an excellent scientific
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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PhD Candidate to conduct research on Artificial Intelligence for managing Shipbuilding Supply Chains
by the Research Council of Norway and the partners for the period 2026-2030. There will be approximately 25 doctoral scholarships and some postdoc positions. Duties of the position Complete
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, including physics-informed neural networks, neural operators, hybrid physics-ML approaches, and emerging foundation-model paradigms for scientific data. Scientific machine learning is increasingly important
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the position We are seeking a highly motivated PhD candidate to investigate cascading cyber effects, cyber resilience, and advanced cyber range modelling. The research combines simulation, software
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to investigate cascading cyber effects, cyber resilience, and advanced cyber range modelling. The research combines simulation, software development, and experimental validation in the Norwegian Cyber Range
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This PhD project, part of the REACT MSCA Doctoral Network, aims to develop an energy-efficient compute-in-memory (CIM) architecture using gain-cell memory for real-time edge learning, addressing
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. This leaves manufacturers and battery management system developers with limited data on which to define safe operating windows, while the computational models intended to predict plating–stripping dynamics