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Experience with firm level econometric analyses or with processing of large firm level datasets will be an advantage, but it is more important that you have experience with software tools such as Stata, SAS, R
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frameworks. Should be comfortable working with machine learning methods and tools for model development and evaluation. Embedded systems, real-time computing, hardware-software co-design, and hardware-oriented
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software development. Qualification requirements PhD stipends are allocated to individuals who hold a Master's degree. PhD stipends are normally for a period of 3 years. It is a prerequisite for allocation
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self-motivation, and a genuine interest in environmental issues, design, and AI. Preferably, the candidate has experience with relevant software/AI tools and/or environmental science. Relevant
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. Experience working with Finite Element Method (FEM) tools, such as Abaqus, ANSYS, OrcaFlex, or similar software, is highly regarded. Furthermore, an interest or practical experience in additive manufacturing
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robotics software frameworks such as ROS/ROS 2. You will be expected to work both independently and collaboratively in an international research environment, with excellent written and spoken English skills
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for these projects has excellent academic qualifications, strong self-motivation, and a genuine interest in environmental issues, design, and AI. Preferably, the candidate has experience with relevant software/AI