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, an interest in mapping the specialized translation landscape in hosts, and a willingness to learn, teach, and troubleshoot techniques in a team environment. Responsibilities 60%- Virology assays and cell
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project has a strong focus on developing and applying machine learning and computational methods for protein design, in close integration with experimental enzymology and biocatalysis. The tasks include
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(SHORES) and the Division of Engineering, New York University Abu Dhabi, seek to recruit a Postdoctoral Associate to work on a fascinating project focused on the development machine-learning powered digital
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experience working with mice. · Proficiency in English (communication, writhing, and presentation). · Interest in learning new techniques. Does this position have supervisory responsibilities? No Preferred
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procedural skills. Team player, willing to help and collaborate on other projects. Preferred Qualifications: Experience with, or interest in, learning modeling neural pathways related to deep brain stimulation
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the best interest of our communities. We are encouraged to Be Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by
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motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in bioinformatics, deep learning and/or biomedical image and clinical data analysis
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. Expertise and knowledge in AI deep learning model development on histology whole slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and
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Description Within the ANR HEBBIAN contract, the objective is to adapt bio-inspired Hebbian learning models recently proposed by one of the partners of this ANR (Frédéric Lavigne) in order to account for data
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learning [3,4]. Indeed, the sensors can be represented as a graph, where each node corresponds to a sensor and the edges represent the relationships between the sensors. These relationships can be spatial