Real-Time Deep Learning for X-ray Spectroscopy

Real-Time Deep Learning for X-ray Spectroscopy

Part-Time 30000 - 40000 £ / year (est.) No working from home possible
N

At a Glance

  • Tasks: Develop deep learning algorithms for real-time X-ray spectroscopy analysis.
  • Company: Join a leading research university in the North East of England.
  • Benefits: Flexible part-time role with opportunities for academic growth.
  • Other info: Collaborative environment with access to innovative research projects.
  • Why this job: Make a real impact in cutting-edge research and technology.
  • Qualifications: Undergraduate degree in science; PhD preferred; Python programming skills required.

The predicted salary is between 30000 - 40000 £ per year.

We are a world class research-intensive university. We deliver teaching and learning of the highest quality. We play a leading role in economic, social and cultural development of the North East of England. Attracting and retaining high-calibre people is fundamental to our continued success.

Does your expertise lie in data science techniques and/or theoretical spectroscopy? Do you have a passion to develop your knowledge to transform the analysis of X-ray spectroscopy using Deep Neural Networks? If so, we would love to hear from you.

We are seeking to recruit a part-time research associate to advance the development of deep neural networks for real-time spectroscopic analysis. Based in Chemistry at Newcastle University, as a Research Associate you will develop and use supervised machine learning/deep learning algorithms to transform the analysis of X-ray spectroscopy by developing and using easy-to-use, computationally inexpensive, and accessible tools for the fast and automated analysis of X-ray spectroscopy. This builds upon recent proof-of-concept work we have performed.

You will have an undergraduate degree in a relevant science subject, preferably chemistry, physics or computer science; a PhD in computer science, theoretical or computational chemistry or a related discipline (candidates who have submitted their thesis will be considered). You will also have expertise in calculating spectroscopic observables or implementing deep learning algorithms as well as experience with a computer programming language, preferably Python.

This is a part-time position. The duration of the appointment will be initially 12 months. The start date is flexible but ideally will be before September 2024.

To apply, please complete the online application, and provide evidence of how you meet the essential criteria required for the role outlined in ‘The Person' by uploading a letter of application along with your Curriculum Vitae (CV).

Informal approaches can be made to Prof. Thomas Penfold.

Information about the group can be found at: http://www.penfoldgroup.co.uk. For further details about Newcastle University please visit our information page at: http://www.ncl.ac.uk/about. For more information about the School of Natural and Environmental Sciences please click here.

Real-Time Deep Learning for X-ray Spectroscopy employer: Newcastle University

Newcastle University is an exceptional employer, renowned for its commitment to high-quality teaching and research. Located in the vibrant North East of England, we foster a collaborative work culture that encourages innovation and professional growth, offering unique opportunities to engage in cutting-edge research in X-ray spectroscopy. Our part-time research associate role not only allows you to contribute to transformative scientific advancements but also provides a supportive environment for personal and academic development.

N

Contact Details:

Newcastle University Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Real-Time Deep Learning for X-ray Spectroscopy

Tip Number 1

Network like a pro! Reach out to people in your field, especially those connected to Newcastle University. Attend relevant events or webinars and don’t be shy about introducing yourself. You never know who might have the inside scoop on job openings!

Tip Number 2

Show off your skills! Create a portfolio showcasing your work with deep learning and X-ray spectroscopy. This could be anything from projects you've completed during your studies to personal experiments. Having tangible evidence of your expertise can really set you apart.

Tip Number 3

Prepare for interviews by brushing up on common questions related to machine learning and spectroscopy. Practice explaining complex concepts in simple terms, as you might need to communicate your ideas to non-experts. Confidence is key!

Tip Number 4

Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Make sure to tailor your CV and cover letter to highlight how your skills align with the role. We’re excited to see what you bring to the table!

We think you need these skills to ace Real-Time Deep Learning for X-ray Spectroscopy

Data Science Techniques
Theoretical Spectroscopy
Deep Neural Networks
Supervised Machine Learning
Deep Learning Algorithms
Computational Chemistry
Spectroscopic Observables Calculation

Some tips for your application 🫡

Show Your Passion:When writing your application, let your enthusiasm for deep learning and X-ray spectroscopy shine through. We want to see how your passion aligns with our mission to transform analysis in this field!

Tailor Your CV:Make sure your CV highlights relevant experience and skills that match the job description. We’re looking for expertise in machine learning and programming, so don’t hold back on showcasing your achievements in these areas.

Craft a Compelling Cover Letter:Your cover letter is your chance to tell us why you’re the perfect fit for this role. Be specific about how your background in chemistry, physics, or computer science makes you a strong candidate for advancing our research.

Apply Through Our Website:Don’t forget to submit your application through our website! It’s the easiest way for us to review your materials and get you into the process. Plus, it shows you’re serious about joining our team.

How to prepare for a job interview at Newcastle University

Know Your Stuff

Make sure you brush up on your knowledge of deep learning and X-ray spectroscopy. Familiarise yourself with the latest research, especially the proof-of-concept work mentioned in the job description. Being able to discuss these topics confidently will show your passion and expertise.

Showcase Your Skills

Prepare to demonstrate your programming skills, particularly in Python. You might be asked to solve a problem or explain how you've implemented deep learning algorithms in past projects. Have examples ready that highlight your experience and how it relates to the role.

Ask Insightful Questions

Interviews are a two-way street! Prepare thoughtful questions about the research group, ongoing projects, and future directions. This not only shows your interest but also helps you gauge if the position is the right fit for you.

Tailor Your Application

When submitting your application, make sure your CV and cover letter clearly outline how you meet the essential criteria. Use specific examples from your academic and research experience that align with the job requirements to make your application stand out.