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be clinically tested in a small animal model. (Ref: PID2022-136961NB-I00)(HR25-00225). Main functions: Design, fabrication, and optimization of liquid-walled pumps (Qpump) capable of achieving
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, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening. Benefits Statement Washington University in St
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, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening. Benefits Statement Washington University in St
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 2 months ago
; Circuit analysis & modeling: Analysis of cortical connectomes, including comparative analyses across ages/regions; hypothesis-driven tests of discovered circuit rules; pair analyses with data-constrained
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/anion exchange membrane systems). The successful candidate will contribute to the design, fabrication, testing, and characterization of materials and devices for clean energy conversion and storage
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form of hybrid human–AI writing that also involves navigating artificially generated text. Through a qualitative text and classroom design, we examine writing with generative AI tools in Danish L1
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simulations is an advantage. The workplace is DTU Lyngby Campus. Postdoc 3 In this project, we will investigate corrosion of materials exposed to MSR fuel salts. We will establish and perform immersion tests
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: ● Automate coagulant dosing and water and gas flows in AguaClara treatment plants. ● Calibrate, test, and iterate the design of a next-generation turbidity meter (Arduino-based with radio communication to a
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We are seeking a talented and motivated Postdoctoral Research Associate (PDRA) to join the Energy and Power Research Group for a 12-month appointment to develop, implement and test a numerical model
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Inria, the French national research institute for the digital sciences | Bron, Rhone Alpes | France | 7 days ago
. Test model predictions in behavioral experiments. Investigate how principles of biological adaptability can inform the design of efficient and robust learning algorithms for artificial systems