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Prof A J Millar
Prof V Danos
Applications accepted all year round
Competition Funded PhD Project (European/UK Students Only)
About the Project
The supervisory team: Prof. Andrew Millar FRS, School of Biological Sciences (main supervisor); Prof. Vincent Danos, School of Informatics, Director of SynthSys; Dr. Robert Muetzelfeldt, Simulistics Ltd.
This fully-funded PhD provides dual-expertise training in the interdisciplinary environment of SynthSys, with experience at Simulistics Ltd.
Understanding the growth of a plant in a changing environment is demanding, because plant development and metabolism respond sensitively to the local conditions. We have linked Crop Science and Systems Biology approaches to understand whole-plant growth, in the first ‘Framework Model’ of the laboratory model plant Arabidopsis thaliana. The model predicts whole-plant biomass, from detailed molecular mechanisms, and was recently validated in independent experiments.
This project will develop the next-generation model, both as a tool for fundamental biology, and to enable synthetic biology designs that take account of the complex regulation in the plant host. You will be trained to use a range of cutting-edge models, building on the concrete example of our Framework Model. The model will be extended to represent larger, molecular networks that control biomass under a wider range of environmental conditions, with international collaborators and Simulistics’ Simile software. You will validate the model in new experiments, using Arabidopsis mutants and environmental control will test the model’s predictive power, and to disseminate the models in the international research community.
Student profile: background in Biology, Geoscience, Agricultural Engineering or a suitably numerate discipline (e.g. computer science, engineering, applied maths or physics). Computer skills essential; programming experience desirable but not essential.
This fully-funded PhD provides dual-expertise training in the interdisciplinary environment of SynthSys, with experience at Simulistics Ltd.
Understanding the growth of a plant in a changing environment is demanding, because plant development and metabolism respond sensitively to the local conditions. We have linked Crop Science and Systems Biology approaches to understand whole-plant growth, in the first ‘Framework Model’ of the laboratory model plant Arabidopsis thaliana. The model predicts whole-plant biomass, from detailed molecular mechanisms, and was recently validated in independent experiments.
This project will develop the next-generation model, both as a tool for fundamental biology, and to enable synthetic biology designs that take account of the complex regulation in the plant host. You will be trained to use a range of cutting-edge models, building on the concrete example of our Framework Model. The model will be extended to represent larger, molecular networks that control biomass under a wider range of environmental conditions, with international collaborators and Simulistics’ Simile software. You will validate the model in new experiments, using Arabidopsis mutants and environmental control will test the model’s predictive power, and to disseminate the models in the international research community.
Student profile: background in Biology, Geoscience, Agricultural Engineering or a suitably numerate discipline (e.g. computer science, engineering, applied maths or physics). Computer skills essential; programming experience desirable but not essential.
Funding Notes
Fully funded for UK and UK-resident EU students through a BBSRC industrial CASE studentship.
Interested individuals must follow the instructions at this link on how to apply
http://www.ed.ac.uk/schools-departments/biology/postgraduate/pgr/how-to-apply
Please contact [Email Address Removed] for informal enquiries.
Interested individuals must follow the instructions at this link on how to apply
http://www.ed.ac.uk/schools-departments/biology/postgraduate/pgr/how-to-apply
Please contact [Email Address Removed] for informal enquiries.
References
www.synthsys.ed.ac.uk; http://www.simulistics.com; http://www.plasmo.ed.ac.uk; http://www.amillar.org.
Salazar J.D., Saithong T., Brown P.E., Foreman J., Locke J.C.W., Halliday K.J., Carré I.A., Rand D.A., Millar A.J. (2009) Prediction of Photoperiodic Regulators from Quantitative Gene Circuit Models. Cell, 139: 1170-1179.
Salazar J.D., Saithong T., Brown P.E., Foreman J., Locke J.C.W., Halliday K.J., Carré I.A., Rand D.A., Millar A.J. (2009) Prediction of Photoperiodic Regulators from Quantitative Gene Circuit Models. Cell, 139: 1170-1179.
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Career overview
Professor Andrew J. Millar received a BA Hons (I) in Genetics from the University of Cambridge between 1985 and 1988, followed by a PhD from The Rockefeller University in New York from 1988 to 1994. He completed a post-doctoral fellowship at the University of Virginia in the NSF Centre for Biological Timing from 1994 to 1995. Professor Millar then worked at the University of Warwick from 1996 to 2004, where he held positions as lecturer, reader, and professor in the Department of Biological Sciences. He was a BBSRC Research Development Fellow from 2002 to 2007 and served as Programme Manager of the Interdisciplinary Programme for Cellular Regulation during 2003-2004. Since 2004, he has been a Professor of Systems Biology at the University of Edinburgh's School of Biological Sciences. He was the Director of the Centre for Systems Biology at Edinburgh from 2007 to 2011 and has been the Associate Director of SynthSys since 2012. Professor Millar was elected to EMBO Membership and the Fellowship of the Royal Society in 2011, and he has served as the Chief Scientific Advisor on Environment, Natural Resources and Agriculture for the Scottish Government from 2018 to 2021. His research has focused on systems biology, particularly in relation to plant biology and chronobiology, and he has been involved in various interdisciplinary research initiatives and science policy efforts.
Research interests
Professor Millar's research focuses on systems biology, particularly in the areas of science policy, research community organisation, and open research. They supervise the Bio_RDM team, which advocates for open research methods in biology and integrates data management with mathematical modelling in systems biology and plant science. Current research interests include the practical aspects of mission-oriented research management, particularly in the context of the UK Chronobiology community and the BioClocks UK initiative. Past research interests involved understanding the 24-hour biological clock in plants, particularly in *Arabidopsis thaliana* and *Ostreococcus tauri*, utilising molecular genetics, transgenic plants, and mathematical modelling to explore the dynamics of biological rhythms and their implications for plant life. Professor Millar has also been involved in interdisciplinary research linking plant science with economics and food security.
Systems Biology
Open Research
Research Data Management
Science Policy
Research Community Organisation
Interdisciplinary Research
Chronobiology
Plant Science
Mathematical Modelling
Data Analysis
Crop Science
Ecology
Biological Timing
Rhythmic Timeseries Analysis
Data Sharing
Software Development
Food Security
Economics
Macroeconomic Environment
Research Cultures
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