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paradigms in primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science
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machine learning are desirable, applicants from other quantitative fields (e.g. math, physics, statistics, computer science) who are eager to learn about neuroscience are highly encouraged to apply as well
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for the development and implementation of innovative statistical and machine learning approaches for analysis of genetics and genomics data. We are particularly interested in applicants who have experience with methods
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• Effective communication skills Preferred Qualifications • Expertise in one of the following areas: Environmental or Performance Physiology, Machine Learning, Motion Analysis, Multiscale Modeling
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
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Remote Sensing; Machine Learning Models for Predicting Wildfire Spread; Wildfire Risk Assessment Through Multi-Modal Data Integration; Automated Vegetation and Fuel Load Mapping Using Computer Vision; AI
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at Université Paris-Saclay (https://cvn.centralesupelec.fr/ ), Prof. Pock from the Institute of Computer Graphics and Vision at Graz University of Technology (ICG ), Prof. Thiran from the EPFL Signal Processing
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computing, and parallel programming paradigms Strong publication record in reputable avenues Strong writing skills Strong skills in model development, data analytics, machine learning, and visualization
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University Munich (www.tum.de). Accordingly, we are currently searching for PhD Students and Postdocs to join our team! PhD Students For PhD students, we are looking for persons that are willing to learn and