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at https://www.linkmetabolism.com . Your tasks: Engineering and optimization of microbial strains for cyanophycin production using thermo-switches and CRISPR-based tools. Integration of targeted and
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bacteria. This is a collaborative project with the Mager Lab (immunology). You can find more information about our group at https://www.linkmetabolism.com . Your tasks: Construction and screening of CRISPR
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HBIGS Heidelberg Biosciences International Graduate School | Mannheim, Baden W rttemberg | Germany | 6 days ago
, which form a critical interface between the circulation and the local tissue milieu, and their age-related functional insufficiency was recently reported to precede organismal aging (https
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ETHOS.HiSim, a python package to simulate households and building systems. Identification of techno-economic data for buildings, retrofitting options, heating and cooling systems, and the building stock
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of Excel is required, and knowledge of other programming languages (Python, R) is a plus Experience working with military and/or foreign aid data Excellent English skills. No German skills required
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environments, e.g., Python, R, Microsoft Azure AI Studio, RapidMiner, Dataiku, etc. Methodological and statistical competencies (e.g., for analytics) Experience with cloud platforms such as Amazon Web Services
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related field Solid understanding of machine learning, especially deep learning and transformer models Practical experience with Python and ML frameworks (e.g., PyTorch, HuggingFace, NumPy, sklearn) Basic
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strong interest in foundational research very good programming skills, preferably in Python good written and spoken English skills We offer: The position comes with access to high performance computing
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The LIT - Leibniz Institute for Immunotherapy (foundation under civil law) (https://lit.eu/ ) – is a biomedical research centre focusing on translational immunology in the fields of cancer
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evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference - implementation of your machine learning pipeline in Python (using e.g