PhD Fellowship in modelling the spread and control of African swine fever
Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences at University of Copenhagen is offering a PhD Fellowship in modelling the spread and control of African swine fever to start on 1 April 2019 or as soon as possible thereafter. The position is limited to three years.
African swine fever is a contagious viral disease of pigs and wild boar of increasing importance within Europe. Despite considerable efforts to control the disease, ASF continues to spread and reached Western Europe in 2018. The limited success of previous control efforts is mainly due to the ability of the virus to survive for long periods in organic material, the persistence of the virus within wild boar populations, and spread of virus over long distances via human activity. In countries such as Denmark with a large swine industry that is based on exports of live animals and animal products, infection with ASF has the potential for considerable economic impact. It is therefore essential that preparatory measures are taken to minimize the eventual impact of ASF incursion events within Denmark. A fundamental part of these preparatory measures is the use of stochastic modelling tools to understand the likely spatio-temporal patterns of disease spread following incursion within Denmark, and to assess the likely impact of different disease control measures on halting spread of the disease.
A stochastic and spatio-temporal simulation model (DTU-DADS-ASF) for the spread of ASF between domestic pig farms was developed, and has subsequently been used to evaluate control measures against the spread of the disease in the Danish context. However, there are critical weaknesses in the model, including the lack of transmission via wild boar that is known to have considerable impact on the spread and persistence of ASF, and the potential for ASF spread via mechanical vectors. Including these elements in the model will improve our ability to understand and predict the dynamics of ASF spread within Denmark, and crucially will allow us to more accurately evaluate control measures to limit the spread of the disease. The end result of this project will have considerable impact within epidemiological research as well as wider society.
The aim of the project is to use an existing stochastic and spatio-temporal simulation model of the spread of ASF in Denmark from which to develop an updated model including the potential for maintenance and spread of the disease within wild boar, transmission between wild boar and domestic pigs, and spread of ASF via mechanical vectors. The successful candidate will bear primary responsibility for programming the model, including all relevant testing and validation of the code, although assistance and guidance will be available from supervisors and other colleagues with a strong background in programming using both R and C++. The model will then be used to assess the epidemiological and economic consequences of an epidemic of ASF in Denmark, and the cost-effectiveness of a set of strategies to control the spread of the diseases will be evaluated. Inference from the model will be used to improve the current contingency plan in Denmark, and will also be useful to aid in the control of the disease in other countries.
African swine fever is a highly relevant subject and is often debated in the media, so the results of this PhD project will be of substantial interest for a variety of researchers and other stakeholders at both the national and international level.
The work will be carried out within a section that is internationally recognised for ongoing work in veterinary disease control, epidemiology and biostatistics, with substantial links to industrial partners within Denmark as well as international researchers in the field. The section comprises individuals from a variety of backgrounds, and with daily activities spanning the whole spectrum from veterinary field work, data wrangling and visualization using a variety of data sources including ‘big data’, statistical analyses and Bayesian modelling, mathematical modelling using deterministic and stochastic models, and statistical software development and programming using compiled languages. This PhD project is a part of a larger project involving several professors, senior researchers, another PhD student and a post-doctoral researcher. The other PhD student and the post-doc will generate data to inform the model. The PhD student is therefore expected to collaborate with project partners, although no direct data collection activities are anticipated unless the successful candidate shows a particular interest in these activities.
Professor Tariq Halasa
Associate Professor Matthew Denwood
Senior advisor Anette Boklund
- A candidate (MSc) degree in Animal Science, Quantitative Ecology, Engineering, Maths, Physics, Applied Statistics, or other relevant subject
- Good programming skills in R are essential for this position
- Previous experience using C/C++ is strongly preferred
- Previous experience using revision control systems (e.g. GitHub or GitLab repositories) and test-based development would be an advantage
- High motivation and basic scientific skills are essential
- Good communication skills in English (both oral and written)
- Good collaborating skills are essential
General Job description
- Your key tasks as a PhD fellow at Faculty of Health and Medical Sciences (SUND) are to:
- Manage, carry through and conclude your research projects
- Actively participate in PhD courses
- Write scientific articles and finalize your PhD thesis
- Participate in international congresses
- Conduct a research stay at an institution abroad
- Teach and disseminate your research
- A highly important research topic, aiming to improve Contingency planning, animal health and welfare.
- A scientific environment with highly dedicated colleagues from wide academic backgrounds
- An international work atmosphere with a large proportion of non-Danish co-workers
- A research environment that strives to make a scientific and applied difference regarding the health and welfare of animals.
Key criteria for the assessment of candidates
- The grade point average achieved in relevant University degrees
- Professional qualifications relevant to the PhD programme
- Previous publications (if any)
- Relevant work experience
- Other professional activities
- Language skills, including English
- Experience with projects involving complex datasets
The successful candidate is also required to be resourceful and to possess good interpersonal skills.
The application must be submitted in English, by clicking on “Apply online” below and must include the following:
- Cover letter detailing your motivation and background for applying for the specific PhD project
- Diploma and detailed transcripts of records
- Other information for consideration, e.g. list of publications (if any), peer reviewed and other
- Personal recommendations (if any)
- A maximum of 3 relevant scientific works which the applicant wishes to be included in the assessment (if any)
The further process
Shortlist: After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Appointments Committee. All applicants are then immediately notified whether their application has been passed for assessment by an expert assessment committee. Selected applicants are notified of the composition of the committee and each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.
For more information click "LINK TO ORIGINAL" below.
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