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have, or will be close to completing, a PhD (or equivalent professional qualifications) with strong quantitative research methods in a relevant discipline (e.g. gerontology, statistics, demography
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conducting high-quality and innovative research addressing complex health and social care challenges of the 21st century. We employ traditional statistical and epidemiological methods, alongside cutting-edge
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multidisciplinary team conducting high quality and innovative research addressing complex health and social care challenges of the 21st century. We employ traditional statistical and epidemiological methods
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inclusive academic community. Opportunities for professional development and career growth, e.g., mentorship of PhD students, development of funding applications, involvement in teaching activities
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numerical models and statistical processing techniques to establish patterns and future trajectories of global change. The post holder will be expected to be able to locate, curate and manipulate time-series
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listeners. We are seeking candidates with a Ph.D. (either awarded or nearing completion) or equivalent professional qualification and experience in Machine Learning, Statistics, or a related field, who have
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statistical and epidemiological methods, alongside cutting-edge artificial intelligence algorithms to gain insights into real-world problems. This is combined with qualitative research to provide deeper
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multidisciplinary team conducting high quality and innovative research addressing complex health and social care challenges of the 21st century. We employ traditional statistical and epidemiological methods
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Heller (Mech Eng). You need to have a PhD in Acoustics, Sound and Vibration Engineering, Human Factor, or a related discipline. Experience in designing and conducting acoustic or vibration measurements and