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the Job related to staff position within a Research Infrastructure? No Offer Description Ref.: 537011 Work type: Full-time Department: Department of Electrical and Computer Engineering (14300
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Ref.: 537011 Work type: Full-time Department: Department of Electrical and Computer Engineering (14300) Categories: Senior Research Staff & Post-doctoral Fellow, Research Staff Applications
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image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed to ample
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slide imaging analysis in computational pathology is essential. Applicants should have a solid publication record and demonstrated experience in computer vision or analysis of pathology images
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public health would be highly desirable. Knowledge and skills in mathematics, biostatistics, advanced statistical techniques in clinical research, database management, and machine learning/artificial
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statistical techniques in clinical research, database management, and machine learning/artificial intelligence (AI) would be an advantage. The appointee will work with the Principal Investigator on various
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learning. He/she will be responsible for literature review, preparation of assessment materials, liaise with external parties, coordination of research activities, conducting assessments with children and
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of public health, biostatistics, pharmacoepidemiology and epidemiological studies. They must be proficient in data analysis using statistical or computer modelling software, such as Stata or R. They should
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experience. Applicants who are in the process of completing a Ph.D. degree will also be considered. Desirable qualifications include physics deep learning, digital twin, smart and resilient infrastructure
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, responsible and able to work independently and within a team. The appointee will work on various projects related to children’s and adolescents’ mathematics and science learning. Duties include literature