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an advantage. A good command of analytical expertise and data science is beneficial. Experience with sustainability assessment, planetary boundaries, and scenario modeling is considered an advantage. Strong
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, innovative, and collaborative PhD fellow with: A recent academic education with a master’s degree in biochemistry, biomedicine, molecular biology, protein science, analytical biochemistry, or similar field
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applications Strong analytical and problem-solving skills Good communication skills and ability to collaborate across disciplines Motivation to make a real-world impact in sustainable energy and industrial
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Cadence Virtuoso, Spectre, or Mentor Graphics. Understanding of semiconductor device physics, especially MOSFET operation, modeling, and scaling. Strong analytical and problem-solving skills, with
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architectures. Add some more digital skills Experience with EDA tools such as Cadence Virtuoso, Spectre, or Mentor Graphics. Strong analytical and problem-solving skills, with the ability to work independently
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; Synopsys or Mentor Graphics. Strong programming skills: Python and C/C++. Experience in hardware accelerators, in-memory processing, or SoC integration. Strong analytical and problem-solving skills, with
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from conventional materials (e.g., traditional metals), two-dimensional materials, and their combinations. The project will employ a broad spectrum of analytical, semi-analytical, and numerical
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of semiconductor device physics, especially MOSFET operation, modeling, and scaling. Strong analytical and problem-solving skills, with the ability to work independently and in collaboration with multidisciplinary
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Digitalisation. The candidates will be responsible for researching the field of Supply chain operations analytics, more specifically focusing on understanding and assessing the role of agentic AI for supply chain