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- Tasks: Engage in cutting-edge research on Bayesian Uncertainty Quantification with expert supervision.
- Company: Join the University of Exeter, a leading institution known for its innovative research and academic excellence.
- Benefits: Enjoy fully funded PhD positions with opportunities to collaborate with the Alan Turing Institute.
- Why this job: Be part of a dynamic research community tackling real-world challenges in health and engineering.
- Qualifications: Candidates should have a strong background in mathematics or related fields.
- Other info: Applications close on 13th May 2019, so act fast to secure your future!
The predicted salary is between 36000 - 60000 £ per year.
Funded PhD Positions in Bayesian Uncertainty Quantification at the University of Exeter
Apr 14, 2019
The University of Exeter Mathematics department is offering up to 4 fully funded doctoral studentships for 2019/20 entry. Full details of the funding awarded, eligibility and a list of all possible projects is available here
There are two advertised projects in Bayesian Uncertainty Quantification, both co-supervised by Professor Peter Challenor and Dr Daniel Williamson. One entitled “Matching covariance kernels to numerical models in Gaussian process emulation” (full description here ), the other entitled “Calibration of numerical models with deep Gaussian processes” (full description here ). Both projects will enable the successful candidate to engage with the Alan Turing Institute for Data Science and Artificial Intelligence, and to join an active group of researchers in Bayesian methods for Uncertainty Quantification for complex models, with applications in Earth system science, human health and engineering.
Applications close on the 13th May 2019.
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Funded PhD Positions in Bayesian Uncertainty Quantification at the University of Exeter employer: The International Society for Bayesian Analysis
Contact Detail:
The International Society for Bayesian Analysis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Funded PhD Positions in Bayesian Uncertainty Quantification at the University of Exeter
✨Tip Number 1
Familiarise yourself with the specific projects being offered, especially the ones supervised by Professor Peter Challenor and Dr Daniel Williamson. Understanding the nuances of these projects will help you articulate your interest and how your background aligns with their research.
✨Tip Number 2
Engage with current or past PhD students in the Mathematics department at the University of Exeter. They can provide valuable insights into the application process and what the supervisors are looking for in a candidate.
✨Tip Number 3
Showcase any relevant experience you have with Bayesian methods or uncertainty quantification in your discussions. This could be through previous research, coursework, or projects that demonstrate your capability in this area.
✨Tip Number 4
Network with professionals in the field of data science and artificial intelligence, particularly those associated with the Alan Turing Institute. Building connections can provide you with additional support and potentially strengthen your application.
We think you need these skills to ace Funded PhD Positions in Bayesian Uncertainty Quantification at the University of Exeter
Some tips for your application 🫡
Understand the Projects: Take the time to thoroughly read the project descriptions for both advertised projects in Bayesian Uncertainty Quantification. This will help you tailor your application to demonstrate your interest and relevant skills.
Highlight Relevant Experience: In your CV and personal statement, emphasise any previous research experience, particularly in Bayesian methods or related fields. Mention specific projects or coursework that align with the PhD topics.
Craft a Strong Personal Statement: Your personal statement should clearly articulate your motivation for applying, your understanding of the field, and how your background makes you a suitable candidate for the funded PhD positions.
Check Application Requirements: Ensure you meet all eligibility criteria and have all necessary documents ready, such as academic transcripts, references, and proof of English proficiency if applicable. Double-check the submission guidelines on the University of Exeter's website.
How to prepare for a job interview at The International Society for Bayesian Analysis
✨Understand the Research Projects
Familiarise yourself with the specific projects on Bayesian Uncertainty Quantification. Be prepared to discuss how your background and interests align with the topics of 'Matching covariance kernels to numerical models in Gaussian process emulation' and 'Calibration of numerical models with deep Gaussian processes'.
✨Showcase Your Technical Skills
Highlight any relevant technical skills or experience you have, particularly in Bayesian methods, data science, or programming languages commonly used in research. This will demonstrate your capability to contribute effectively to the projects.
✨Engage with Current Research
Stay updated on recent developments in Bayesian methods and uncertainty quantification. Being able to reference current literature or ongoing research at the Alan Turing Institute can show your enthusiasm and commitment to the field.
✨Prepare Questions for Your Interviewers
Think of insightful questions to ask Professor Peter Challenor and Dr Daniel Williamson about their research and the PhD programme. This not only shows your interest but also helps you assess if the position is the right fit for you.
