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to annotated cell types Experience of working with non-model organisms, where reference resources are incomplete and annotation cannot be taken for granted Strong programming skills (e.g. R and/or Python) and
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MS data analysis using software such as FragPipe and DIA-NN, as well as basic programming skills in Python. Practical experience in antibacterial assays based on dilution or diffusion methodologies
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of large-scale biological datasets will be considered a strong advantage. Experience with CRISPR-based approaches or statistical programming in R or Python is desirable but not required. The application
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, for example in Python, C++, and an interest in further developing these skills, the ability to work independently and in a structured manner; good collaboration skills, good oral and written communication
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to organic synthesis and properties of organic molecules, is an advantage. good knowledge of data curation and plotting, electronic laboratory notebooks, Python or similar, are merits. excellent grades from
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in Electrical or Mechanical Engineering, Computer Science, or a related subject. Proficiency in C++, Python, and ROS 2 is required. Strong scientific skills with proven excellence in real-life
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To be qualified for the position, you must have an MSc degree in Electrical or Mechanical Engineering, Computer Science, or a related subject. Proficiency in C++, Python, and ROS 2 is required. Strong
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. In addition, the following are requirements for the role: Strong programming and quantitative skills, particularly in Python and/or R. Experience in deep learning, machine learning, or large-scale
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of cladding hoop stress and assessment of PCI-failure risk, • implementing, testing and documenting computational tools, for example in Python, and contributing to reproducible computational workflows
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higher education credits (ECTS). Relevant courses include, for example, image processing, computer vision, machine learning, deep learning and neural networks, as well as courses in Python, GPU programming