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and problem-solving skills are important, and previous experience or interest in coding (for example in R or Python) would be a clear advantage since the project involves handling and interpreting
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6. of this Notice. Preferred factors: Knowledge in machine learning and programming (Python), deep learning (e.g., tensorflow, pytorch) and time-series modeling in marine ecology applications
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is possible in collaboration with other members of the lab. Desired (but not absolutely required) skills: programming in python, machine learning, and experience in protein structure analysis. Required
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and Computer Vision Excellent programmer in Java / C / Python or equivalent Excellent at using Machine Learning software, e.g. PyTorch / TensorFlow / Scikit Learn Highly knowledgeable in mathematical
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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their response to different environments, we try to replicate different environments under controlled laboratory conditions. By systematically confronting users with such environments, we aim to identify and
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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, TensorFlow) and protein language models. Experience with programming (Python preferred) for bioinformatics or data science applications. Exposure to degradomics methods or post-translational modification
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candidates must meet the requirements for an MSc degree. Good verbal and written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and
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systems. Proven programming skills in Python, R, or a comparable language. Interest in developing methodologies to assess localized climate hazards, exposure, and vulnerability as inputs to impact-based