Research and Development Specialist in AI/Machine Learning for Image Analysis | Luxembourg City, Luxembourg | University of Luxembourg

Position:	Research and Development Specialist in AI/Machine Learning for Image Analysis
Institution:	University of Luxembourg
Location:	Luxembourg City, Luxembourg
Duties:	The junior group in Imaging AI develops applied AI research focused on biomedical signal analysis and medical image computing. The general aim of the group is translating bleeding edge algorithms from fundamental AI and imaging research closer to a concrete biomedical application. A focus is currently towards more robust AI models for applied image computing, for example by employing domain adaptation, joint embedding architectures, or similar techniques
Requirements:	At least a Master’s degree in computer science or related discipline; Strong background in software development in relevant languages (Python, MATLAB); Interest in applied machine learning, including but not limited to deep learning; Interest in image analysis/computer vision and pattern recognition, including but not limited to biomedical applications, in particular for neuroscience; Experience with recent deep learning frameworks (e.g. Pytorch, MONAI)

Text:	Research and Development Specialist in AI/Machine Learning for Image Analysis The junior group in Imaging AI develops applied AI research focused on biomedical signal analysis and medical image computing. The general aim of the group is translating bleeding edge algorithms from fundamental AI and imaging research closer to a concrete biomedical application. A focus is currently towards more robust AI models for applied image computing, for example by employing domain adaptation, joint embedding architectures, or similar techniques At least a Master’s degree in computer science or related discipline; Strong background in software development in relevant languages (Python, MATLAB); Interest in applied machine learning, including but not limited to deep learning; Interest in image analysis/computer vision and pattern recognition, including but not limited to biomedical applications, in particular for neuroscience; Experience with recent deep learning frameworks (e.g. Pytorch, MONAI)