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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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, demonstrated experience of coding in programming languages such as R and Python is considered particularly advantageous. Examples of computationally intensive methods central to IAS and IDA are data-driven text
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and developing (generative) AI to improve software development processes as well as the quality of software artefacts (e.g., code or designs). We are, therefore, looking for a candidate with experience
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empirically validate how GenAI agents can assist software developers in tasks such as code generation, documentation, optimization, and human-AI interaction workflows. As a postdoctoral researcher, you will be
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code for the Eclipse Arrowhead. Projects typically involve working with both academic and industrial partners in Europe. Hence, collaboration with the software and automation industry in the form of both
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automation architecture and the use of AI and Machine Learning (ML). Targeted results include academic papers and contributions with open-source code for the Eclipse Arrowhead. Projects typically involve
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automation architecture and the use of AI and Machine Learning (ML). Targeted results include academic papers and contributions with open-source code for the Eclipse Arrowhead. Projects typically involve
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experiments to evaluate protein self-assembly. An ability to derive equations and writing code to analyze data on protein self-assembly. Practical experience in measuring protein size distributions and
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at compile-time, as is often the case, then the problem is further complicated by the fact that no single mapping is optimal for all combinations of matrix sizes. As a consequence, any code generated
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the case, then the problem is further complicated by the fact that no single mapping is optimal for all combinations of matrix sizes. As a consequence, any code generated (at compile-time) to evaluate