The Animal and Plant Sciences is one of the leading research departments for whole-organism biology in the UK. The department research projects in locations from the Polar Regions to the tropics, at scales from within cells up to entire ecosystems. Through our research we aim both to understand the fundamental processes that drive biological systems and solve pressing environmental problems. The Bioinformatics Hub is a new establishment aiming to develop novel computational tools and carry bio statistical analyses. Dr. Elhaik’s lab has a diverse range of activities from Molecular Evolution to Paleo genomics (see www.eranelhaiklab.org).
You will take part in the most exciting research in population genetics – understanding the story of humans. You will develop biostatistical models to help us understand the story of mankind over the past 10,000 – 1,000 years. You will analyse modern genetic data from worldwide populations and develop likelihood-based tools to predict their similarity based on geographical origins. Nearly all the studies of Dr. Elhaik in population genetics have received wide media coverage and some have been ranked as the most read; both in their respective journals and compared to all other papers. Dr. Elhaik’s work has been featured on TV, radio, journals such as Science and Nature; and popular newspapers like: The Times and the Economist. It was commented on by the Vatican, leading scientists, and state leaders. To read about the impact of the work done so far see (http://www.eranelhaiklab.org/ -> Press).
You will have a good honours degree in biostatistics, computational biology, computer science, biomathematics, or similar degrees and experience of conducting research e.g. through a qualification or through a previous research assistant post or through working towards a PhD. Ideally you will have experience in analysing quantitative data and a relevant postgraduate qualification (or relevant experience) featuring research methods. You can view the supporting documentation by clicking on About the Job and About the University located near the top of your screen
Learn more about the position here.
You can apply from the University of Sheffield Job’s website. Vacancy code: UOS012021