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Inria, the French national research institute for the digital sciences | Nantes, Pays de la Loire | France | about 18 hours ago
Research Infrastructure? No Offer Description The successful candidate will join a dynamic and international research team (https://stack.inria.fr ). As a research engineer, you will contribute to the design
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for general-purpose workloads in standard distributions, and that interact in poorly documented ways with the Python runtime, its garbage collector, and the memory allocation patterns of data science libraries
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biology or a closely allied discipline along with experience in creating, writing, enhancing, and running code in R/Python, using and developing microfluidic devices and advanced imaging. You will have
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the detection of anomalies in the manufacturing process of unique industrial components. Different alternatives will be explored and analyzed, in the field of machine learning, that allow relevant information
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on what characterizes intelligence in humans and AI and develop neuro-cognitive methods and formal models to describe the similarities and differences? Join us! We are looking for a PhD candidate to join
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photonic imaging and patch-clamp electrophysiology. The postdoctoral fellow will contribute in particular to different aspects: - in vivo calcium imaging (ex vivo imaging approaches and patch-clamp
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deployment enabling validation and demonstration of real-world applications. For more details, please view https://www.ntu.edu.sg/erian We are looking for a Senior Research Fellow to develop a CFD engine and
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materials. · Interest in electrochemistry, solid‑state ionics, high‑throughput experimentation and data‑driven research methodologies. · Basic familiarity with Python, data analysis or machine‑learning
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Award. Overseas applicants are welcome to apply, however will need to cover the tuition fee difference. Further information on tuition fees can be found on the following webpage - https://sheffield.ac.uk
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methods (e.g., difference-in-differences, instrumental variables, propensity-score methods) and selected machine-learning algorithms. Write reproducible code in Stata, R, SAS, or Python; summarize and