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highly motivated candidate who meets the following qualifications and characteristics: PhD (completed or soon to complete) in Software Engineering, Computer Science, Artificial Intelligence, or a closely
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will lead efforts to apply state-of-the-art AI techniques (machine learning, deep learning, generative models, etc.) to the discovery and development of new materials in critical domains: water, energy
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, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks
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activities within the areas of embedded software. The position requires a PhD degree within a relevant area (e.g. software, computer, or control engineering) and the desired candidate is expected to have
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. The candidates will be responsible for collaboratively building up the area of supply chain digitalisation with a primary focus on data governance, artificial intelligence, and applied machine learning. Successful
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environmental modelling, including data science methods such as AI and machine learning Proficiency in GIS and R programming or similar Effective communication skills and experience working with authorities
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observations, and remote sensing data to assess the impact of global change on ecosystem productivity and sustainability. You will develop novel algorithms to integrate data-driven machine learning and process
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value theory, non- and semiparametric statistics, missing data problems, causal inference, graphical models, event history analysis, benchmarking, spatio-temporal modelling, machine learning, and
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activities, which span a diverse range of advanced electronic systems. These include FPGA and neuromorphic computing, edge AI, machine learning, sensing technologies, and energy harvesting—key components
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and Python); Ability to work productively both independently and as part of an interdisciplinary team. An interest and willingness for learning new methods and technologies in a fast moving and highly