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Science Programs, and MS in Computer and Information Science (https://cse.aua.am/ ) invite applications for a full-time faculty position in Machine Learning at the rank of Assistant Professor, starting in
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Training Group Information (JTT) https://arxiv.org/pdf/2107.09044 [3] Hacohen, Weinshall (2019). On the Power of Curriculum Learning in Training Deep Networks http://proceedings.mlr.press/v97/hacohen19a
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Join us at the forefront of life science AI. We are looking for a postdoctoral researcher to develop cutting‑edge, multimodal transformer‑based deep learning methods to extract insight from genomic
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Natural History. The researcher will develop deep learning models to predict individual bee age based on wing morphology. This model will be trained of existing wing images and applied to images of museum
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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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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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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