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                background in preferably more than one of the following areas: Thermodynamic analysis and simulation of energy technologies/processes/systems Programming tools such as Python, Matlab, Modelica, Pytorch, etc 
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                questions about the position, you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost. Further information We recommend that you save a copy of the job posting, 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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                position, you are more than welcome to contact us. You will find contact persons at the bottom of the jobpost. Further information We recommend that you save a copy of the job posting, as it will be removed 
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                caused by the exposure to diverse simulated weather scenarios and urban traffic loadings. Responsibilities Your responsibility is twofold. First, it is driving and performing the research efforts as 
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                (28nm or below) Hardware-aware modeling of state-space inference pipelines Simulation and synthesis of the architecture using EDA tools Benchmarking against transformer-based hardware accelerators Work 
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                Hardware-software co-simulation and benchmarking This PhD project is part of SDU microelectronic unit’s effort in neuromorphic chip design and collaborates with international partners working on spiking AI 
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                tools such as RFdiffusion2 or BoltzDesign. Perform molecular dynamics simulations and in silico screening to assess inhibitor-target interactions and predict selectivity. Clone, express, and purify top 
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                of thermodynamic modelling, process simulation is an advantage. For applicants to the PhD position, you must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent 
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                emphasizes innovation through the development of a Virtual Learning Environment (VLE) for construction safety or disaster response simulation, integration of Information Backbones including Digital Twins and