Job Summary Table of Data-driven Models Research: Postdoc Opportunity

Job Description Summary

Queen Mary University of London is seeking a talented Postdoctoral Research Assistant to join an innovative project developing data-driven models for reactive flows. This role offers a unique opportunity to contribute to cutting-edge research in collaboration with Kyushu University, Japan.

🔬 Responsibilities

• Develop a reduced-order surrogate model for predicting ammonia direct injection spray characteristics
• Utilize hybrid machine learning approaches in model development
• Collaborate with international research partners, particularly Kyushu University
• Conduct modeling and simulation of three-dimensional multiphase turbulent reacting flows
• Apply and develop machine learning tools for chemical kinetics and turbulent combustion
• Contribute to academic publications and presentations
• Assist in project management and reporting

🌟 Benefits and Perks

• Competitive salary range of £40,223 – £47,178
• 30 days’ leave per annum
• Access to a pension scheme
• Season ticket loan scheme
• Enhanced family-friendly leave policies
• Personal development opportunities
• Collaborative and diverse work environment

🏫 Company Overview

Queen Mary University of London is a world-renowned institution committed to fostering social justice and improving lives through academic excellence. With a rich reformer heritage, the university embraces diversity of thought and opinion, believing that when perspectives intersect, truly original ideas take form.

🌈 Company Culture

At Queen Mary, we cultivate an environment where:

• Ideas can come from anywhere
• Diversity is celebrated and valued
• Interdisciplinary collaboration is encouraged
• Social justice and global impact are prioritized
• Innovation and academic excellence thrive side by side

🚀 Career Growth Opportunities

This postdoctoral position offers excellent prospects for career advancement, including:

• Collaboration with leading researchers in the field
• Opportunities to publish in high-impact journals
• Participation in international conferences and workshops
• Development of cutting-edge skills in data-driven modeling and machine learning
• Potential for future academic or industry leadership roles

🤝 Diversity, Equity, Inclusion, and Belonging

Queen Mary University of London is deeply committed to creating an inclusive community where everyone can thrive. We actively promote diversity in all its forms and strive to create an environment where all voices are heard and valued.

⚖️ Equal Opportunity Statement

Queen Mary University of London is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, gender, sexual orientation, gender identity or expression, age, national origin, disability, or any other protected characteristic. We are committed to building a diverse and inclusive workforce that reflects the communities we serve.

🏠 Remote Work Policy

This position is primarily on-site at the Queen Mary University of London campus. However, the university recognizes the importance of work-life balance and may offer flexible working arrangements where appropriate.

📝 Application Process

1. Review the job description and ensure you meet the qualifications
2. Prepare your CV and a tailored cover letter
3. Submit your application through the online portal
4. If shortlisted, participate in an interview (provisional date: 16 September 2024)
5. Complete any additional assessments as required
6. Await the final decision

⏰ Application Deadline

The application deadline is 15/08/2024, 23:55. We encourage early applications as the position may be filled before the closing date if an exceptional candidate is identified.

📨 How to Apply

To apply for this exciting opportunity, please visit the Queen Mary University of London job portal and follow the application instructions. For any queries, please contact Dr Amin Paykani at a.paykani@qmul.ac.uk.

🌐 Social Media Links

• LinkedIn
• Twitter
• Facebook

❓ FAQs or Additional Information

Q: Is visa sponsorship available for this position?

A: Please contact the HR department for specific information regarding visa sponsorship.

Q: What is the duration of the contract?

A: This is a fixed-term contract for 30 months.

Q: What are the working hours?

A: The position is full-time, with 35 working hours per week.

Q: Where will I be based?

A: The role is based at the Queen Mary University of London campus in London, UK.

Q: What department will I be working in?

A: You will be part of the School of Engineering and Materials Science, specifically within the Centre for Intelligent Transport (CIT).

This postdoctoral research assistant position in data-driven models for reactive flows presents an exceptional opportunity for a talented researcher to contribute to groundbreaking work in computational physics and engineering. As part of Queen Mary University of London’s esteemed research community, you’ll have the chance to collaborate with international partners, develop cutting-edge models, and advance your career in a supportive and dynamic environment.

The project’s focus on developing reduced-order surrogate models for ammonia direct injection spray characteristics using hybrid machine learning approaches is at the forefront of current research in this field. Your work will have significant implications for the understanding and optimization of reactive flows, potentially leading to advancements in various industries, including energy and transportation.

By joining this project, you’ll be part of a larger effort to drive innovation in transport and mobility technologies, contributing to a more sustainable and efficient future. The interdisciplinary nature of the work, combining elements of mechanical engineering, applied mathematics, and computer science, offers a rich learning experience and the opportunity to develop a diverse skill set highly valued in both academia and industry.

Queen Mary University of London’s commitment to diversity, inclusivity, and social justice creates an ideal environment for personal and professional growth. The university’s reformer heritage and emphasis on bringing together diverse perspectives foster an atmosphere of creativity and innovation, where your ideas will be valued and your potential can be fully realized.

If you’re passionate about pushing the boundaries of computational physics, excited by the prospect of working with state-of-the-art machine learning techniques, and eager to contribute to impactful research with global significance, this postdoctoral position could be the perfect next step in your career. Apply now to be part of this exciting journey at the intersection of data science and reactive flow modeling.

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