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-Cas gene editing Pooled CRISPR screens Preparation of deep sequencing libraries for functional genomics Targeted protein degradation and induced proximity therapeutics Protein quantification and
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to the eDIAMOND project’s goals (see Job description section above). Theoretical and practical experience and passion in at least one of the following topics: Machine Learning: Deep Learning, Federated Learning
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Mathematics, Statistics, Physics, or other quantitative discipline Solid programming skills Fluency in both spoken and written English is mandatory Ideal Qualifications Experience with deep learning frameworks
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design tools, finite element simulation tools, topology optimization tools, path planning and slicing tools, etc.); Experience with programming, preferably Python; Deep enthusiasm for conducting original
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scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Required Skills: Strong analytical background Proficiency in geometric deep learning and machine learning Prior experience in physics-informed
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Solid programming skills Fluency in both spoken and written English is mandatory Ideal Qualifications Experience with deep learning frameworks (such as JAX/PyTorch/TensorFlow) Strong background in modern
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topics: Machine Learning: Deep Learning, Federated Learning (vertical, horizontal), Split Learning, Model Selection, Knowledge Distillation, Low-Rank Adaptation (LoRA), Large Models (Language, Vision
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Sciences, Geological Engineering, Geography, Geophysics, or a related field A strong interest in gaining a deep understanding of geomorphic processes, natural hazards and their dynamics Proficiency in data
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or related discipline, who has a deep understanding of landscape and/or Baukultur and is skilled in programming. Ideal candidates have experience with LiDAR data and point cloud data manipulations. Furthermore