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- Tasks: Develop innovative non-reversible MCMC methodologies and collaborate with top researchers.
- Company: Lancaster University, a leading institution in research and education.
- Benefits: Competitive salary, diverse work environment, and opportunities for professional growth.
- Why this job: Join a cutting-edge research team and make a real impact in computational statistics.
- Qualifications: Strong background in MCMC and programming skills required.
- Other info: Flexible starting date and commitment to diversity in the workplace.
The predicted salary is between 32958 - 38183 £ per year.
A Senior Research Associate position for up to three years dedicated to developing new methodologies in non-reversible Markov chain Monte Carlo (MCMC) and led by Dr Chris Sherlock is now available. In collaboration with Dr Sherlock and members of the team at the National University of Singapore and the University of Glasgow, the postdoctoral researcher will develop new, efficient non-reversible algorithms, test and analyse them, both by simulation and theoretically, and implement them in an easy-to-use package.
Most standard MCMC algorithms, such as the Metropolis Hastings algorithm, are reversible. However, it is now well established that non-reversible MCMC algorithms can have substantially better mixing properties, particularly for the high-dimensional and complex models that are common in modern applications. Developing general purpose non-reversible MCMC algorithms is currently one of the most active areas of computational statistics.
A good understanding of standard, reversible MCMC is essential, as is a proven proficiency in computer programming.
Starting date: 1 November 2017 or a later date by arrangement.
We welcome applications from people in all diversity groups.
Senior Research Associate at Lancaster University, UK 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 Senior Research Associate at Lancaster University, UK
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Lancaster University, especially those in the Mathematics & Statistics department. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Prepare for the interview by brushing up on your MCMC knowledge. We should be ready to discuss both reversible and non-reversible algorithms in detail. Practising common interview questions can help us feel more confident.
✨Tip Number 3
Showcase our programming skills! If we have any projects or code samples related to MCMC, let’s have them ready to share. This will demonstrate our proficiency and passion for the subject.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure our application gets noticed. Plus, we can tailor our application to highlight how our skills align with the role.
We think you need these skills to ace Senior Research Associate at Lancaster University, UK
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Research Associate role. Highlight your experience with non-reversible MCMC and any relevant programming skills. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about developing new methodologies in MCMC. We love seeing enthusiasm and a clear understanding of the role, so let your personality come through.
Showcase Your Skills: Don’t forget to showcase your proficiency in computer programming and your understanding of standard MCMC algorithms. We’re keen on candidates who can demonstrate their technical skills effectively, so be specific about your experiences.
Apply Through Our Website: Remember to apply through our website! It’s the best way to ensure your application gets to us directly. Plus, you’ll find all the details you need to complete your application smoothly.
How to prepare for a job interview at The International Society for Bayesian Analysis
✨Know Your MCMC Inside Out
Make sure you brush up on your understanding of both reversible and non-reversible MCMC algorithms. Be ready to discuss their properties, advantages, and potential applications in detail. This will show that you're not just familiar with the theory but can also apply it practically.
✨Showcase Your Programming Skills
Since proficiency in computer programming is crucial for this role, prepare to discuss your experience with relevant programming languages and tools. Bring examples of past projects or code snippets that demonstrate your ability to implement algorithms effectively.
✨Engage with the Team's Research
Familiarise yourself with the work being done by Dr Chris Sherlock and the team at the National University of Singapore and the University of Glasgow. Mention specific papers or projects during the interview to show your genuine interest and how you can contribute to their ongoing research.
✨Prepare Thoughtful Questions
Interviews are a two-way street, so think of insightful questions to ask about the team's methodologies, future projects, or the challenges they face in developing non-reversible MCMC algorithms. This not only shows your enthusiasm but also helps you gauge if the position is the right fit for you.
