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DC-26094– POSTDOC/DATA SCIENTIST – AI-DRIVEN CLIMATE RISK MODELLING AND EARLY WARNING SYSTEMS FOR...
applicant will contribute to the AIGLE project by: · Developing innovative scientific Deep Learning/Machine Learning algorithms for flash flood forecasting. · Contributing to the collection
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. Work within identified processes to complete tasks efficiently and accurately. Be responsible for maintaining standard operating procedures, learning materials, task cards, and onboarding packages. What
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working at NYU please visit our website at: http://www.nyu.edu/about/careers-at-nyu.html . NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040. Learn more at nyu.edu
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programming skills in Python or C++, and practical experience with deep learning libraries (e.g., PyTorch) Desirable criteria 1. Research experience in one or more of the following areas: tactile sensing
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distribution. Develop and enforce procedures that align automation systems with daily logs, conduct daily/weekly checks on the video server and digital asset management system, and acquire program files from
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following areas: Strong foundation in machine learning, optimization, and deep learning algorithms, including Transformer architectures. Hands-on experience or solid theoretical knowledge of LLMs/SLMs
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learning and genomics. Specifically, the candidate will work on developing and applying cutting edge deep learning frameworks for modeling massive single cell and bulk multi-omic datasets. Duties include
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engineering or similar. Knowledge and experience with deep learning models applied in computer vision. Remarkable academic trajectory, validated by a strong record of publications in relevant international
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particular the research lines of Professors Seppe vanden Broucke (e.g., applications of deep learning, graph learning, geospatial analytics, process mining), Frederik Gailly (e.g., ontologies, knowledge graphs
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candidates in the area of Business Analytics, with particular interest in those applying machine learning and deep learning methods to business domains, such as HR analytics, marketing analytics, and