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rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is characterized by close
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; developing and optimizing doping protocols for conjugated polymers and other organic semiconductors; correlating materials chemistry and microstructure with electronic performance; implementing the resulting
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teaching in key and rapidly evolving areas such as autonomous systems, data-driven modeling, learning-based control, optimization, complex networks, and sensor fusion. Research at the division is
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communication limitations, adversarial conditions, continual and adaptive learning in dynamic environments. The research will combine tools from distributed optimization, stochastic approximation, information
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in clinically relevant environments. Key work assignments include: Design, fabrication, and optimization of high-performance plasmonic nanostructures and SERS substrates for sensing in complex
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, network science, and decentralized machine learning. Welcome to read more about us at: https://liu.se/en/organisation/liu/isy/ks . For more information about working at ISY, please visit: https://liu.se/en
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models and algorithms in Python, with documented experience in PyTorch. The applicant should be knowledgeable with neural networks and furthermore have a strong drive towards performing fundamental