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: Solid background in analog/mixed-signal ultra low power CMOS circuit design, including experience with amplifiers, data converters, and bias circuits. Experience with industry-standard EDA tools such as
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models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train these methods in a closed-loop
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of enzyme activity. Publish results in high-impact journals and present findings at scientific conferences. Engage in interdisciplinary training to build expertise in both computational and experimental
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addressing key sustainability challenges such as climate, biodiversity, water use or land use These tasks require experience in life cycle assessment and/or absolute environmental sustainability assessment
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• Knowledge of statistics and/or data science • Knowledge of Matlab, Python, or a similar programming language • Some research experience (e.g., in the form of a conference contribution, a publication, or a
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in both written and spoken English. You should be ambitious, hardworking, and driven by a passion for scientific excellence. Previous experience with silicone polymers, elastomers, or foam processing
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forward to receiving your application and potentially welcoming you to our center. Head of center, Professor, Bo Nørregaard Jørgensen If you experience technical problems, please contact hcm-support@sdu.dk
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engines. Knowledge of advanced combustion concepts is a merit but not a prerequisite. Practical experience of engine operation in a lab is a merit. Knowledge of control theory is a merit and even better is
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background in CMOS/VLSI design, computer architectures (preferred RISC-V architecture), and deep learning principles. Experience with industry-standard EDA tools such as Cadence suite: Genus, Virtuoso, Spectre
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for experimental research and data analysis. Excellent written and oral communication skills in English are prerequisites. Additionally, experience with programming and/or mathematical modelling is an advantage. Due