17 high-performance-computing positions at Linköping University in Ireland-University-Ranking-2024
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qualifications required for employment as associate professor. The Division of Cybersecurity (CYBER) at the Department of Computer Science conducts research as well as undergraduate and doctoral education within
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performance of materials and devices. Contribution to scalable fabrication of multi-cell devices and their validation using representative low-grade heat sources. Analysis and interpretation of experimental
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optimization of the electrical, electrochemical, mechanical, and energy-conversion performance of materials and devices. Fabrication and validation of multi-cell devices under representative low-grade heat
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-learning frameworks, such as PyTorch, and high-performance computing (HPC) environments. Knowledge of molecular and cellular biology, systems biology, or precision medicine. Finally, a letter of intent
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Investigate the electronic, optical, and magnetic (including magneto-optical) properties of materials (qubits). Device fabrication Use materials as qubits in quantum computing and related fields, single photon
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Sweden 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 a Research
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high-resolution mass spectrometry, in vitro pharmacological characterisation of new psychoactive substances, as well as metabolomics and machine learning. As a PhD student, you devote most of your time
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on delivering high-quality work. The following education, experience and expertise are required: A Master Level Degree in Migration Studies or related field Knowledge of ethical guidelines for research
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to a higher education programme in Bachelor or Master level. We are looking for someone with knowledge and an interest in cybersecurity. The following qualifications are required: Relevant knowledge
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will be devoted to practical problems in economics and finance, like the construction of high-dimensional optimal portfolios. Motivated by the widespread application of sample generalized inverses in