Vacancies
Open vacancies are displayed below, but if you are interested keep an eye on this space. If you would like to apply for funding for a fellowship or studentship externally to join our group, please contact me with the sort of topic you are interested in and the sort of funding you have in mind applying for.
Please note, I am a mathematical biologist and have a wide interest but can only supervise projects which have a modelling component.
Please note, I am a mathematical biologist and have a wide interest but can only supervise projects which have a modelling component.
PhD Studentships
Please find details of current and past studentships below. Please click [+] to read more...
How to dry seeds: developing a mathematical model for the seed drying process and predicting the quality of dried seeds
**CLOSED** Deadline January 2016. A fully funded PhD studentship on the interface of mathematical modelling and seed processing Supervisory team: Prof. Vincent Jansen (RHUL), Prof. Michael Stumpf (Imperial College), Dr Christophe Grosjean (Syngenta), Dr Tina Steinbrecher (RHUL), Prof. Gerhard Leubner (RHUL) The production of seeds is an important part of the growing crops. After seeds are harvested, they are cleaned, dried, treated and stored, resulting in a product that can then be passed on to growers. During the processing, seeds can be damaged. The drying process, for instance, can cause significant damage to seeds, resulting in reduced germination or vigour of the seeds. The aim of this project is to provide a quantitative understanding of the damage that occurs during seed processing through the formulation and analysis of a mathematical model for the seed drying process, and to use this model as a tool to predict damage during the drying process. During the seed drying process water is removed. How long to dry for depends on temperature and relative humidity. The longer the drying time to more likely that the seed is damaged, either through microbiological infection, or mechanical damage. Elevated temperature can have negative effects of seed quality, and can lead to loss of vigour and reduced seed germination. The combination of these factors means that there are optimal. How precisely these factors interact is not known. In this project we will conceptualize the seed drying process to develop a mathematical model for the seed drying process, and formulate a quantitative description of the rate of damage versus time and temperature, relative humidity and drying rate. Currently very few models exist to describe this, here we aim to develop approaches and provide a mechanistically underpinned models for the seed drying process that will allow us to generate a statistical description of the amount of damaged that occurs. With this we aim to predict the quality of seeds at the end of the drying process. The quantity we aim to predict is the probability that a seed will germinate, and have sufficiently vigour at the end of the drying process. Once these models are formulated we will confront them with data from the seed drying process in order to develop it into a modelling tool that will allow us to predict the seed quality as a function of the operating parameters during the drying process. A particular challenge in estimating parameters is that certain, so called sloppy, parameters, can be difficult to estimate. In this project we will use build on recent insights in model selection and on the identifiability of parameters to overcome the challenges to generate predictions with parameters with limited identifiability. In this project we will combine mathematical modelling (Jansen, RHUL), Bayesian statistics (Stumpf, Imperial College) with process studies (Grosjean, Syngenta) and seed biology (Leubner, Steinbrecher, RHUL) to further our understanding of the seed drying process and to try to develop a statistical rigorous predictive methodology for the damage occurred in seed drying and for the optimisation of the drying process. This research will have potential impact on the commercial production of seed for crops and vegetables. |
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Further details for projects:
These projects are suitable for candidates with some background or experience in mathematical modelling, or simulation at undergraduate level. We are looking for candidates, either with a background in the life sciences, and experience in mathematical or simulation modelling or Bayesian statistics, or for candidates with a background in a quantitative subject (e.g. mathematics, statistics, computer science, physics) and an affinity for research in biology.
This PhD studentship is funded for 3 years. Applicants are expected to hold, or to be awarded a first class or a good upper second class BSc Degree, Masters or an equivalent qualification in a relevant field by October 2016. An additional year of fully funded Masters level training may be offered to eligible BSc applicants. The course will commence in October 2016. Funding includes an annual tax-free stipend at the standard Research Council rate (£16,057 for 2015-2016, to be confirmed for 2016-2017 but typically increases annually in line with inflation) and covers tuition fees at the UK/EU rate. To be eligible for this studentship, applicant must either be a UK citizen or a European Union national who has been resident in the UK for at least 3 years prior to starting the degree. The studentship will be held in the School of Biological Sciences of Royal Holloway, University of London. The research in the School covers the breadth of biology and hosts a number of theoretical researchers. The scenic Royal Holloway campus is on the outskirts of London.
Apply before the 31th of January following the link
https://www.royalholloway.ac.uk/biologicalsciences/prospectivestudents/studentships/home.aspx
Get in touch with Tracey Jeffries ([email protected]) for any application queries. If you are interested in applying please contact me informally before the deadline at [email protected]
This project is suitable for candidates with some background or experience in mathematical modelling, or simulation at undergraduate level. We are looking for candidates, either with a background in the life sciences, and experience in mathematical or simulation modelling or Bayesian statistics, or for candidates with a background in a quantitative subject (e.g. mathematics, statistics, computer science, physics) and an affinity for research in biology.
This research will build on previous research in the supervisors.
Komorowski, M., Costa, M.J., Rand, D.A. and Stumpf, M.P., 2011. Sensitivity, robustness, and identifiability in stochastic chemical kinetics models. Proceedings of the National Academy of Sciences, 108(21), pp.8645-8650
An example of the use of model selection by the Jansen research group:
Jansen, V.A., Mashanova, A. and Petrovskii, S., 2012. Comment on Lévy walks evolve through interaction between movement and environmental complexity. Science, 335(6071), pp.918-918.
This PhD studentship is funded for 3 years. Applicants are expected to hold, or to be awarded a first class or a good upper second class BSc Degree, Masters or an equivalent qualification in a relevant field by October 2016. An additional year of fully funded Masters level training may be offered to eligible BSc applicants. The course will commence in October 2016. Funding includes an annual tax-free stipend at the standard Research Council rate (£16,057 for 2015-2016, to be confirmed for 2016-2017 but typically increases annually in line with inflation) and covers tuition fees at the UK/EU rate. To be eligible for this studentship, applicant must either be a UK citizen or a European Union national who has been resident in the UK for at least 3 years prior to starting the degree. The studentship will be held in the School of Biological Sciences of Royal Holloway, University of London. The research in the School covers the breadth of biology and hosts a number of theoretical researchers. The scenic Royal Holloway campus is on the outskirts of London.
Apply before the 31th of January following the link
https://www.royalholloway.ac.uk/biologicalsciences/prospectivestudents/studentships/home.aspx
Get in touch with Tracey Jeffries ([email protected]) for any application queries. If you are interested in applying please contact me informally before the deadline at [email protected]
This project is suitable for candidates with some background or experience in mathematical modelling, or simulation at undergraduate level. We are looking for candidates, either with a background in the life sciences, and experience in mathematical or simulation modelling or Bayesian statistics, or for candidates with a background in a quantitative subject (e.g. mathematics, statistics, computer science, physics) and an affinity for research in biology.
This research will build on previous research in the supervisors.
Komorowski, M., Costa, M.J., Rand, D.A. and Stumpf, M.P., 2011. Sensitivity, robustness, and identifiability in stochastic chemical kinetics models. Proceedings of the National Academy of Sciences, 108(21), pp.8645-8650
An example of the use of model selection by the Jansen research group:
Jansen, V.A., Mashanova, A. and Petrovskii, S., 2012. Comment on Lévy walks evolve through interaction between movement and environmental complexity. Science, 335(6071), pp.918-918.