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Field
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connectivity and brain function. You have affinity with working with large datasets and have knowledge of data analysis and programming (MATLAB, Python, R, or other scientific coding/programming). Affinity with
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document their requirements. write filter and other post-processing scripts (Python) to eliminate misleading / useless data parts. document post-processing guidelines to be published along with the dataset
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and programming (MATLAB, Python, R, or other scientific coding/programming). Affinity with computational neuroscience, connectomics and/or Machine Learning is appreciated. Our goal perform connectome
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applications Deploy Python-based applications as services on Linux-based servers, ensuring system security and business continuity Collaborate with researchers, domain experts, and users to integrate LLMs
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their performance. The modelling and implementation shall exploit the latest paradigms in programming and modelling languages, such as Python, Matlab/Simulink, etc. Another option is to exploit Machine Learning
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experience in this area. You have extensive knowledge of: Linux (RHEL/Ubuntu) Ansible Docker Terraform/OpenTofu Kubernetes BASH Python It is an advantage if you have experience with: Hardware management
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, applied mathematics, robotics, or a related engineering field; Good working knowledge of modern C++ and Python – both will be applied in the project; Understanding of algorithms, optimisation methods, and
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for a candidate with: an MSc in computer science, artificial intelligence or a related field a creative and collaborative mindset strong programming skills in Python or Rust strong skills in deep learning
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, (Computational) Epidemiology, Behavior Sciences or a related field; experience with programming and modelling (e.g., Python, R, NetLogo, AnyLogic, or similar); a strong interest in urban health, physical activity
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creative and collaborative mindset strong programming skills in Python or Rust strong skills in deep learning systems strong analytical and problem-solving skills fluency in English, both written and spoken