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Postdoctoral Research Associate I, Psychology (Genetically Informed Studies of Social Connectedness)
opportunities in areas related to the behavior genetic study of social relationships and health. The study involves a complex and sophisticated data collection spanning detailed neuropsychological assessments
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
11.02.2022, Wissenschaftliches Personal The Chair of Information-oriented Control (ITR) offers a PhD/PostDoc position within the 6G-life Research-Hub „Digital transformation and sovereignty
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, including quantitative, qualitative, and experimental approaches. Ideally, experience with Python, Stata, or R. • demonstrates proficiency in data collection, processing, and analysis, preferably using
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on conduction system diseases. To identify these pathways, the postdoc will analyze and integrate data from mouse models for different diseases, human tissue, human iPSC-derived pacemaker-like cells and cutting
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homeostasis. Responsibilities include recombinant protein expression and purification, development and execution of enzyme and biophysical assays, and quantitative data analysis to support structure–function
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Posting Details Position Information Posting Number PG191602PD Position Number 00111796 Position Type Post Doc FLSA Departmental Information Department ID 196001 - Department of Population Health
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experimental independence, including the design and execution of animal studies, development and optimization of molecular and cellular assays, and data analysis and interpretation. Candidates should be
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Posting Details Position Information Posting Number PG191601PD Position Number 00111795 Position Type Post Doc FLSA Departmental Information Department ID 196001 - Department of Population Health
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
on “Integrating AI into Aquatic Ecosystem Models to Decode Ecological Complexity” funded by Villum Fonden. Within that project, the focus is on exploring novel ways to infer information from environmental data
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across connected forest–lake ecosystems. By integrating multi-taxa field data, trait-based ecology, experiments, and advanced statistical analyses, TRACE aims to uncover how ecological processes propagate