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chronic conditions and illnesses. This research aligns with CVDB's public health mission to strengthen evidence supporting improved recognition and characterization of ME/CFS. Learning Objectives: You will
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, diverse group Experience working with standard computer software Previous experience working with and caring for rodents Excellent technical skills for bench work including gene expression analysis, immune
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machine learning approaches relevant to breast cancer research and medical imaging, where appropriate collaborate with multidisciplinary teams including radiologists, radiographers, clinicians
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reactions. Experience applying Machine Learning to optimise and guide iterative laboratory experiments. Experience of oligonucleotide design and of adapting an amplification method to new target sequences
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the assembly, management, and analysis of complex datasets, including the application of machine learning techniques to develop a range of models such as predictive and image-recognition models. A key aspect of
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, microbial cultures, and cleaning validation samples. Develop data analysis pipelines for Raman spectral classification, potentially integrating machine learning methods. Research & Project Responsibilities
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disruptions and in pinched plasma disruptions in dense plasma focus devices. Bremsstrahlung scattering of these energetic electrons orbiting within the machine produce gamma-rays (of energy up to ~20 MeV
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We are looking for a Research Fellow for the CogniVision AI cameras project led by Professor Massimo Alioto, at the Department of Electrical and Computer Engineering, National University
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Principal Investigator and a cell-culture specialist in a friendly, multidisciplinary group spanning optics, electrophysiology, microfabrication and machine learning, collaborating with partners
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our translational efforts is the development of mRNA-based therapeutics, particularly in vivo CAR-T/NK/Macrophage technologies and cancer mRNA vaccines, as well as epitranscriptomics-based biomarkers