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make a difference in the world! Position Information We are seeking a postdoctoral position focused on the development and deployment of computer vision and intelligent robotic systems through physics
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evidencing: which scientific discoveries are more impactful than others; whether public attitudes to science change over time; how the public learn and talk about science; how different target groups respond
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of remedial rules and institutions. Reframing remedies as an intermediary link between different systems crucial in the production of our imaginaries of justice, CURE aims to provide a new reading of labour law
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in Dr. Shanlin Ke’s lab. The overarching goal of Dr. Ke’s lab is to develop computational approaches and leveraging bioinformatics tools, metagenomic sequencing, multi-omics data, machine learning, and
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machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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the development of hierarchical computational materials discovery schemes combining random structure searching, machine learning, atomistic, and density functional theory (DFT) calculations to accurately and
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 38 minutes ago
biogeochemical model using times series forecasting and machine learning. The Post Doc will focus on one or two of the questions depending on their expertise and interest. Minimum Acceptable Education & Experience
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Number: 6375630 Postdoctoral Scholar - Mathematics Location: Syracuse University Campus Pay Range: $60,450 - $62,400 Pay Determination: Salary offers at Syracuse University will be based on education
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on the analysis of different characteristics of the skin and body fluids, such as sweat and blood. Many of these methods are challenged with quality (accuracy/precision of measurement), power consumption, usability