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Field
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in terms of design and technology challenges, application mapping and reliability issues. Thus, there is a growing demand for efficient and reliable digital CIM-based neuromorphic system design which
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, application mapping and reliability and non-ideality issues. Thus, there is a growing demand for efficient and reliable memristor CIM-based neuromorphic system design which includes techniques such as
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., web3.py/ethers.js, Solidity/Vyper, sub-graph indexing), and local development/testing frameworks such as Hardhat, Truffle, and Ganache Basic knowledge of blockchain APIs or analytics platforms (e.g
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Disease and Related Dementias (MAP-AD). This innovative and multidisciplinary project aims to develop brain oganoids derived from human iPSCs- to study vascular dysfunction in Alzheimer’s disease and
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-cell CRISPR screens). Mapping dynamic network rewiring from joint scRNA-seq + scATAC-seq. Identifying state-specific causal networks from population-scale scRNA-seq. We approach single-cell biology as a
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, United States of America [map ] Appl Deadline: 2025/11/15 11:59PM (posted 2025/09/02, listed until 2026/04/05) Position Description: Apply Position Description The Department of Mathematics, College of Arts and Sciences
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academic experience; - Two recommendation letters; - A short CV indicating the link to Google Scholar, Research ID or ORCID profiles. This opportunity is open to candidates of any nationality. The selected
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The Romanian team of the international MAPS project, led
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custom tools and end effectors for robotic assemblyGood knowledge of the CAD software Rhinoceros 3D, its plugin Grasshopper 3D, and its API RhinoCommonReal-world architecture and/or construction
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, or reinforcement learning Proficiency in Python and contemporary software ecosystem for optimization, dada management, and API development Experience with teaching and supervision Experience with IoT, edge computing