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Professional qualifications (required) Relevant PhD degree (e.g. computer science, machine learning, statistics) Experience in developing deep learning models for 3D point cloud data Strong programming skills
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language skills Experience in the following will also count in the assessment of the applicants: computational and statistical methods for analysis; rodent behavioural assays, brain sectioning and
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institution for the duration of the fellowship. Experience with AI-related research and/or innovation is an advantage. A strong background in statistics is required, as well as experience in atmospheric
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background in statistics is required, as well as experience in atmospheric dynamics or climate dynamics, basic shell scripting, and python/Matlab/R or similar languages. Experience with “traditional” climate
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be employed by any other institution for the duration of the fellowship. Experience with AI-related research and/or innovation is an advantage. A strong background in statistics is required, as
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also count in the assessment of the applicants: optogenetics, chemogenetics, computational and statistical methods for analysis; rodent behaviour, histology methods, sleep scoring, neurodevelopment as
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the following will also count in the assessment of the applicants: optogenetics, chemogenetics, computational and statistical methods for analysis; rodent behaviour, histology methods, sleep scoring