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, internal peer equity, as well as market and organizational considerations when extending an offer. PhD For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr
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: This project is related to machine learning for Urban Informatics. In this context, the intersection between the urban infrastructure and digital technologies plays an essential role. The aim is to develop
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apply statistical and machine learning models to identify predictive markers of depression. Design and execute experimental protocols related to self- representation and chronic pain. Prepare manuscripts
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning for improving
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HCI and cybersecurity, to cancer research tools and methods for numerical analysis and machine learning. The research work takes place in a multidisciplinary team with a focus on image processing with
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-performance or cloud computing environments. Need strong data management and database skills, expertise in clinical phenotyping ontologies and the application of machine-learning/AI methods to biomedical data
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Qualifications Certificates/Credentials/Licenses PhD Computer Skills Microsoft Office Supervisory Responsibilities No Required operation of university owned vehicles No Does this position require direct animal or
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expect the candidate to have: PhD in transportation science, machine learning, behavioral economics or a related field. Programming skills Python, along with experience working with transportation
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. Familiarity with statistical modelling, machine learning and deep-learning Additional information: We offer: 🌐The opportunity to work with our state-of-the-art HPC infrastructure and to join a vibrant network
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-performance or cloud computing environments. Need strong data management and database skills, expertise in clinical phenotyping ontologies and the application of machine-learning/AI methods to biomedical data