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Field
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Earth system models on different temporal and spatial scales to answer key questions of global change. Doctoral candidates of the IMPRS-ESM contribute to the development and application of Earth system
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an integrated interdisciplinary PhD programme that consists of three main components: 1. An interdisciplinary research project that combines concepts and methods from different fields. 2. A substantial programme
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Experience with programming (for example Python), including the use of machine learning or any other AI technique Good oral and written presentation skills in Norwegian Personal characteristics To complete a
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Experience with VLSI design (Cadence tools, Verilog/VHDL, SPICE) Knowledge of neural networks and neuromorphic systems is a strong advantage Good programming skills (e.g., Python, MATLAB) and interest in
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ultrabroadband mid-infrared intrapulse difference frequency generation sources. You will perform multispecies detection in demanding applications such as environmental and exposure monitoring, and in the green
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, preferably Reinforcement Learning (e.g., Q-learning, Deep Q-Networks) or other control algorithms. Proficiency in Python, MATLAB, or similar for data analysis, modeling, or AI implementation. Strong written
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. PV field system data analysis (time-series data analysis with JMP software and /or Python). Accelerated ageing procedures (IEC standards). PV module failure modes. Corrosion. Strong communications
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(https://soilsystems.net/ ), a Priority Programme (SPP 2322) funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation). Within SoilSystems, scientists from different disciplines from
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of the largest, most international and most innovative employers in the region. With more than 6000 employees from 100 different countries, we are helping to build tomorrow's world every day. Through top
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inducible pluripotent stem cells (iPSC) cells from patients (healthy and those of patients with cardiovascular diseases) as a platform to investigate the function of different G protein-coupled receptors