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Field
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, statistical signal processing, optimization theory, machine learning and artificial intelligence. The candidate is expected to actively participate in experimental work focused on building datasets of channel
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relations and in interaction with organizations, to gain insight into computer-mediated communication, its applications and effects, and to pursue evidence-based communication strategies, instruments and
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environment project, we will develop automated species and community recognition, particularly focusing on pathogenic soil fungi, with help of deep-learning algorithms fed with microscopic image and Raman
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project. Your profile We are looking for a highly motivated candidate with a background in machine/deep learning, and communication networks. The required qualifications include: PhD in computer engineering
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: Artificial Intelligence / Machine Learning Knowledge Representation and NLP methods Clinical Informatics Bioinformatics Biomedical Ontology Public Health Informatics Nursing Informatics Imaging Informatics
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Postdoctoral Associate to advance cutting-edge research in machine learning (ML). Our lab explores the intersection of artificial intelligence, and human-computer interaction, striving to create technologies
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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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Computer Engineering or a closely related field, completed by the start date of the appointment. Research experience in at least one of the following areas: ● Chip design, tape-out, and testing
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and machine learning with Prof. Jason M. Klusowski (https://klusowski.princeton.edu). The position is for one year with the possibility of reappointment based on satisfactory performance and
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in combination with other machine learning techniques, to create predictive models. You will engage in an interactive feedback loop with domain experts to analyze discovered models and remove any