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fast-paced research environment, a structured and organized approach is highly valued. You will work in a team of researchers from diverse backgrounds, including PhD students and postdocs, and should
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level in electrical engineering, electromagnetic engineering, wireless engineering, engineering physics, applied physics, a closely related field. Good command of electromagnetic simulation tools such as
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CMOS technologies. Well-versed in the end-to-end design flow, including circuit design, simulation, layout, PCB design, and measurement of integrated circuits using advanced CAD tools. Excellent
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flow, including circuit design, simulation, layout, PCB design, and measurement of integrated circuits using advanced CAD tools. Excellent communication skills and proficiency in both written and spoken
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to either first-principles calculations or AI supported database management of high-throughput type calculations/simulations. Basic knowledge of density functional theory (DFT) is beneficial. Strong
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transcripts, both undergraduate and graduate. If the master’s degree is recent, the applicant must submit a Registrar's letter confirming that they have completed the degree. · A copy of your master's thesis
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applications towards materials science. Generative machine learning models have emerged as a prominent approach to AI, with impressive performance in many application domains, including materials discovery
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cancer. The goal will be to find genetic prediction models to be able to predict which childhood cancer patients have a high or low risk of toxicity in childhood cancer. Preliminary the doctoral project
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for interviews will begin on October 1st, 2025. Please include in the application: A motivation letter A detailed Curriculum Vitae, including references that can be contacted Copy of the M.Sc. and bachelor’s
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address outstanding questions on behavioural evolution in canids. Your work assignments Understanding how behaviours evolve is a long-standing goal in evolutionary biology. Using the domestic dog as a model