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Field
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) Experience with plant biochemistry, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2
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-phase fragmentation mechanisms and ion chemistry Interest in computational proteomics, spectral library development, or fragmentation modeling Programming/scripting skills (e.g., Python, R) for data
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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) Experience with plant biochemistry, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2
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characterization will be prioritized. Programming Skills: Working knowledge in standard scripting languages such as R and Python is recommended. Further Technologies: Experience in protein 3D structure prediction
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-conventional microorganisms such as Pseudomonas spp. , Streptomyces spp. , oleaginous yeast such as Yarrowia lipolytica , black yeast (e.g. Exophiala viscosa ), or Fusarium graminearum Species Complex. Python
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Multiphysics, MATLAB, or Python Familiarity with device-level simulations and multi-physics approaches Self-motivated and able to work independently while contributing to a collaborative research environment
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(https://www.classique.aau.dk). CLASSIQUE will address a suite of fresh research challenges defined by the intersection of digital applications that have real-time requirements and quantum resources
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to evolve classical communication networks to support both traditional data and the unique requirements of quantum information systems (https://www.classique.aau.dk). CLASSIQUE will address a suite of
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Intelligence, or a closely related field Solid experience in one or more of the following: NLP, speech processing, human-AI interaction, or agentic-AI systems Strong programming skills in Python and familiarity