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years of experience with extensive expertise in microelectronics and microsystems technology. Our wide range of technologies spans from advanced semiconductor processes and MEMS technologies to innovative
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on semiconductor manufacturing and medical technology. Do you have a passion for developing application-oriented computer vision pipelines for semiconductor metrology? Join our team as a student and
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 8 days ago
, Quantum Engineering or related field # Experience or a strong interest in one or more of the following areas is desirable: # Quantum optics and photonics # Semiconductor materials and device physics
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semiconductor devices and circuits based on fully depleted silicon-on-insulator (FDSOI) technology for next-generation AI hardware. This position focuses on the design, fabrication, characterization, and modeling
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of the shuttled electron [Nat. Commun. 15, 1325 (2024) ] which makes this approach very promising for scaling up semiconductor spin qubit devices [Nature 653, 360 (2026) ]. This position focuses on experimentally
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. You possess solid knowledge of semiconductor technologies, particularly in the areas of MEMS and/or power electronic devices, as well as the associated processes and equipment. You contribute strong
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preferably an engineering background in the field of emerging microelectronic, semiconductor or photonic key technologies who is enthusiastic about contributing to research and teaching in this field. You
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tackle the complex challenges of our time. The Test Group is currently being set up and will be responsible for developing and operationally delivering test solutions for semiconductor devices and
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power electronic systems – from innovative assembly, interconnection, and cooling concepts to advanced circuit topologies and intelligent control algorithms. The use of wide-bandgap power semiconductors
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(PINNs) and Operator Learning Applications of trustworthy AI (e.g. robust modelling of semiconductors and RF power devices) Data Attribution Methods Method development in the areas of: local feature