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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 18 days ago
, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling every nuance of how humans and animals look and move. We develop
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. Support participant recruitment, data collection, and analysis for technology development and testing activities. Liaise with a range of stakeholders including participants, people with aphasia, family
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powered by: Cookie Information Nettsiden bruker cookies Vi ønsker at du skal være trygg når du bruker dette nettstedet. Vi benytter cookies for å sikre at du får en best mulig brukeropplevelse og
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: Electrical and Computer Engineering Employee Category: Research Staff Location: Kent Ridge Campus Posted On: 13/02/2026 ▲ Collapse Job Title: Research Fellow (Topolectrical Circuits and Non-Hermitian Physics
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$66,672, depending on qualifications, experience, department budgets, and industry data. Employees receive more than just a paycheck. University employees enjoy a comprehensive benefits package that
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Pay Grade/Pay Range: Minimum: $53,500 - Midpoint: $66,900 (Salaried E8) Department/Organization: 214251 - Electrical and Computer Eng Normal Work Schedule: Monday - Friday 8:00am to 5:00pm Job
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data: Review data analysis reports with Dr. Kirsten Klein and/or Dr. Tucker Conduct literature searches as needed Lead the coordination of the Student Research Writing Team and provide regular updates
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empirically grounded insights and strategies to support trustworthy data exchange and effective collaboration in emerging DPP ecosystems. The position offers the opportunity to conduct high-impact research
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to the QS Rankings. Further information can be found at www.kaust.edu.sa. ONLY SELECTED CANDIDATES WILL BE CONTACTED BY E-MAIL.
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participants to better understand how bipolar disorder unfolds over time. Combining clinical information, treatment experiences, overall health data, and genetic insights, the study helps identify patterns in