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Field
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intelligence, NLP, machine learning, or a related field Experience with Python and Generative AI libraries (e.g., Huggingface Transformers) Knowledge of Multimodal Generative AI models and their corresponding
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in mechanical engineering, electrical engineering, computer science, AI, or related field, with outstanding study results. DESIRABLE REQUIREMENTS: Programming experience in Python, particular
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information on eligibility requirements. The position requires: The applicant must have strong skills in Matlab or Python -based programming and must be willing to expand their Matlab skills Knowledge about
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tasks would be: Develop and implement Python scripts for the automated control of electron microscopes; design and execute automated experiments, including real-time feedback loops between acquisition and
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dynamics, numerical modeling, and scientific programming is required. The following areas of expertise are considered beneficial: Experience in scientific computations using Python, C, C++. Experience in
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, optimization, deep learning, or information theory; Experience in programming, e.g., in C++, Python or Matlab. Qualification requirements PhD stipends are allocated to individuals who hold a Master's degree. PhD
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processes with relevance for irrigation and drainage Have knowledge in programming in R and Python for statistical analyses and modelling. This includes experience in applying these skills in projects Have
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a completed or in-progress Ph.D Good knowledge of quantitative research methods and data in the social sciences, and statistical programs for handling them (e.g., Python, R, and Stata) Experience
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the application of machine learning and artificial intelligence. By using neural networks developed in Python, the project aims to generate robust and generalisable models for scaffold design. Industrial
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the fields of electron spectroscopy or ion spectroscopy or laser physics is beneficial. Substantial experience in the lab work during master thesis or later is required. Strong skills in Python programming