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Field
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of AI models and LLMs specifically tailored for data mining in the physical sciences and engineering Fine-tuning and evaluation of open-source LLMs (e.g., Teuken 7B, Llama 3, Mistral 7B) specifically
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should have demonstrated in-dependent experience in designing and carrying-out ethnographic fieldwork, and in qualitative data analysis. - Experience with participatory design or participatory
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of climate model output by means of classical statistical and machine-learning methods #coordination of scientific workflows among project partners Your profile #Master's degree and PhD degree in meteorology
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its detailed analysis through Oxford Nanopore Technologies (ONT). Your role will be central in creating and applying bioinformatics and machine learning tools to analyze long-read data and decipher cap
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degree and PhD degree in meteorology, oceanography, physics or mathematics, with a strong interest in the application of statistical and data analysis methods excellent knowledge in UNIX/Linux and Unix
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bring to the table PhD in biotechnology, microbiology, molecular biology, or a related field Experience working with strict anaerobes, ideally with Clostridia Strong hands-on skills in molecular biology
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? The doctoral degree should have been completed no longer than two years before the time of application. Doctoral students finishing their PhD studies by the beginning of the scholarship are also eligible
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of scientific publications and project reports Supervision of PhD students and other students Support in the preparation of third-party funding proposals Support in establishing the institute Your Profile: Master
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(such as MEA) to assess the impact of disease mutations on neuronal biology Collaborate with bioengineers, material scientists, and computational biologists to leverage AI-supported analytical pipelines
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enjoys scientific discussion and interdisciplinary science. To be considered for this position, you must have a PhD in a field like physics and applied mathematics or a field related to one