Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials

Nottingham Trent University; Nottingham; Hybrid; GBP 38,000 - 44,000; Full time

Job summary

Nottingham Trent University is seeking a Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials. The role focuses on developing a platform using computational chemistry and ML to understand the dynamics of molecular materials, offering a fixed-term contract with competitive salary and extensive benefits.

Benefits

30 - 35 days annual leave plus bank holidays

Flexibility in working patterns

Salary Sacrifice Retirement Savings Plan

Health and wellbeing services

Formal and informal professional development opportunities

Qualifications

• PhD in relevant field required.
• Essential experience in Python (ASE, scikit-learn, pytorch).
• Experience in uncertainty quantification or stats advantageous.

Responsibilities

• Develop machine learning platform to assess isomerization effects.
• Analyze adsorption and diffusion in porous molecular framework materials.

Skills

Python

Uncertainty Quantification

Statistics

Education

PhD in Chemistry, Materials Science, Physics or related field

Job description

Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials

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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials

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Postdoctoral Researcher in Machine Learning of Porous Molecular Framework Materials

Grade H

£38,394 - £43,188 p.a. pro rata

1 year fixed term contract

About The Role

Molecular Framework Materials (MFMs) are of strong interest worldwide due to their porosity, crystallinity and chemical functionalizability / tunability making them appealing for a broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis.

A major drawback when applying computational chemistry to MFMs is that, even for "rigid" MFMs, especially when functionalized, their structures are disordered due to the random orientation of linkers. Such structural disorder and flexibility are well-known in crystallography, but less in computational chemistry, where a distinct structure is required to undertake a calculation. This problem has largely been ignored, and researchers have chosen a single “representative” MFM

structure, ignoring positional disorder which makes the calculation feasible but at the cost of ignoring the local structure. This is problematic, as the local structure has strong effects on guest binding, diffusion and even the dynamic behaviour of the entire MFM.

In this project, funded by the Leverhulme Trust, we will develop a machine learning platform to describe the the effects of isomerization on adsorption and diffusion in porous Molecular Framework Materials (e.g. MOFs, COFs, ZIFs, MOPs...).

The project extends from our initial work on developing desciptors for isomerization in MOFs: https://doi.org/10.1039/D3QI01065A

What we are looking for:

• A PhD in Chemistry, Materials Science, Physics or a related field
• Experience in python (ASE, scikit-learn, pytorch) is essential
• Experience in uncertainty quantification or statistics applied to quantum chemistry and machine learning would be advantageous
  
  

For more details, please take a look at the role profile. We'll still consider applications even if you don't meet every single one of the requirements, so don't be put off if you don't match them perfectly.

Interviews; w/c 14th July

About Us

The School of Science and Technology at Nottingham Trent University (NTU) is an exciting multidisciplinary environment for learning, teaching and research, with some of the best facilities in the UK.

We pride ourselves on delivering high-quality teaching and diverse, real-world research. We specialise in biosciences, chemistry, computing and technology, as well as engineering, forensic science, mathematics, physics and sport science. This mix of traditional and modern subjects encourages and inspires future innovators.

In the Department of Chemistry, courses are taught in modern, innovative spaces, offering excellent career prospects and accreditation by The Royal Society of Chemistry. The Department has an active research community with a diverse range of knowledge and expertise.

For any informal queries about the role, please contact Dr Matt Addicoat at [e-mail].

Join Us

• 30 - 35 days annual leave per year plus statutory bank holidays and 5 university closure days pro rata
• Hybrid working - we encourage and offer a mixture of office working and working from home. You're empowered to define how you work best for the benefits of your stakeholders.
• Flexibility - take ownership over how you get your work done. We're open to different working patterns and approaches.
• Salary Sacrifice Retirement Savings Plan with life assurance and income protection. Available to colleagues who choose to opt out of the contractual pension scheme. Minimum colleague contributions of 0% matched with minimum NTU contributions of 8%.
• Access to a wealth of formal and informal professional development opportunities to develop your skills and advance your career.
• Range of health and wellbeing services, including a Health Cash Plan, voluntary benefits, discounts, and savings for all colleagues.
• And a whole lot more…Find out more about the range of benefits we offer at Benefits | Nottingham Trent University
  
  

Come and be part of our success. Apply today.

Safe and Inclusive

At NTU, we continue to build an inclusive culture that encourages, supports and celebrates the diverse voices and experiences of our students and colleagues. By championing positive wellbeing, we promote an environment where all can thrive and reach their full potential. We welcome the unique contributions that you can bring and we encourage people from underrepresented communities and backgrounds to apply to join our team.

Please note that unfortunately, this role has been assessed as ineligible for sponsorship under the UK Visas & Immigration points-based immigration system however, we recommend that you assess your eligibility before applying for this position. For more information visit the Government Skilled Worker visa support page. However, applications are welcome from candidates who do not currently have the right to work in the UK, but who would be eligible to obtain a valid visa via another route. Please consult the Home Office website for further information.

Please note that this role is covered by the Rehabilitation of Offenders Act (1974) and successful applicants will be asked to declare any unspent criminal convictions.

Seniority level

• Seniority level

  Internship

Employment type

• Employment type

  Full-time

Job function

• Job function

  Research, Analyst, and Information Technology

• Industries

  Higher Education

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