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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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. You will be part of a network of young researchers in deep learning in the Visual Intelligence Graduate School https://www.visualintelligence.no/about/vigs Jarli & Jordan/ UiO via Unsplash Jarli
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deep learning to support ongoing research projects involving large-scale healthcare and biomedical datasets. The Research Assistant will work closely with faculty on data-driven research, model
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(SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise
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, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap camera footage for wildlife monitoring and conservation efforts. Job Responsibilities
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 24 days ago
. Through advanced Machine Learning and Deep Learning technologies, it seeks to automate agronomic processes, optimize resource use, and maximize production in a sustainable way. Main duties Design
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bioinformatics and genomics is not required; we're targeting talented software engineers who want to expand into the fields of bioinformatics and genomics (visit https://learngenomics.dev/ to learn more about
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ACP’s captured instances on conventional yellow sticky traps. MANIFESTO team will explore advanced and modern Deep Learning (DL) architectures to develop an accurate model for detection and classification
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focuses on single-cell genomics, biotechnology, and bioinformatics. The project involves transcriptomic and genomic profiling of single microbes. The post-doc will work on machine and deep learning methods
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(“overparameterized”) machine learning models, like probabilistic graphical models, deep neural networks, diffusion models, transformers, e.g. large language models, etc. SLT is based on the geometrical understanding