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, or microfluidics. Demonstrated experience in nanoparticle-based biosensor development or SERS sensing platforms. Proficiency in CAD software (e.g., SolidWorks) for microfluidic device design. Experience with Raman
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the outcomes of bioengineering interventions. You will work closely with an interdisciplinary team of bench scientists, automation engineers, and software engineers in devising methods for high-throughput data
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learning or computer vision conferences/journals, such as TPAMI, IJCV, CVPR, ICCV, ECCV, NeurIPS, ICML and ICLR. Knowledge of scientific or engineering software like PyTorch, TensorFlow, Keras, etc. Research
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the statistical analysis using SAS software or R; conduct literature reviews as necessary, prepare tables and figures, and participate in manuscript preparation and presentations; contribute to the development
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systems Working knowledge of ecological (especially landscape ecology) research methodology and advanced biostatistics Computer proficiency, including use of statistical software for spatial analyses
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Integration a. Lead the design and integration of ML-driven diagnostic tools into failure analysis workflows. b. Build robust and scalable software solutions interfacing with diagnostic instruments and test
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top-tier machine learning or computer vision conferences/journals, such as TPAMI, IJCV, CVPR, ICCV, ECCV, NeurIPS, ICML and ICLR. Knowledge of scientific or engineering software like PyTorch, TensorFlow
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: A PhD degree in Civil Engineering or Earthquake Engineering in a closely relevant field. Familiarity with earthquake data, models and software used in earthquake hazard and loss modelling
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software engineering. • Track Record: Strong publication record in leading machine learning, artificial intelligence, data science, or evolutionary computation venues (e.g., ICML, ICLR, NeurIPS, AAAI
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; lip-sync and audio-visual synchronization; evaluation of factuality, citability, WER, MOS and latency; software engineering, version control, containerisation or development pipelines; technical