12 Postdoctoral Fellowship at University of Leeds, West Yorkshire, England

Based in the Institute for Transport Studies at the University of Leeds, you will primarily contribute to the modelling and assessment of electric vehicles. This work aims to derive and assess policy interventions (by developing a modelling and simulation software environment) to increase design and operational efficiency, and reduce energy consumption from electric vehicles (EVs), considering real-world conditions (e.g. transport mission; road topography; weather; and surrounding vehicles).

Joining the Spatial Modelling and Dynamics Research Group and working with Professor Haibo Chen and colleagues, you will specifically work to develop assessment capabilities required for a life cycle analysis of affordable and user-centric frugal electric vehicles equipped with innovations such as lighter mass and eco-sustainable materials, suitable range and dynamic performances, and higher utilisation of local reusable resources.

You are expected to mainly work on the EU-funded project “ZEV-UP: Frugal Zero-Emission Vehicles for the Urban Passenger challenge“. Your research will provide input to the assessment of policy intervention scenarios and strategies for short- and long-term green vehicle uptake in various markets, accelerating the transition to sustainable urban mobility and contribute to the reduction of greenhouse gas emissions in the transport sector. You may also be requested to support relevant research activities in other on-going projects such as nPETS in the field of nanoparticle emissions, transport pollution and health impact.

Are you a creative process chemist looking for your next challenge? Does developing interdisciplinary solutions to poor air quality, a problem affecting the health of thousands of people, motivate you? Do you want to develop your networks both in one of the UK’s leading research-intensive institutions and with industrial partners?

You will join our team from the Schools of Chemistry, and Chemical and Process Engineering, working to develop LowCat, a new catalyst for NO_x emissions mitigation. You will support a late-stage commercialisation project funded by the Science and Technology Facilities Council. The project builds on existing work demonstrating the effectiveness of LowCat for exhaust emissions mitigation and initial scale up of manufacture to the kg scale. The team at University of Leeds are working with partners from University College London, the ISIS Neutron facility and MinChem limited to deliver a scalable process for manufacture of an optimised catalyst to a range of target markets.

You will work closely with process chemistry experts in the Institute of Process Research and Development and at MinChem limited, as well as academic project collaborators, and will lead on the development of a continuous flow process for production of a consistent, optimised product. You will design and construct a novel continuous flow process with reaction monitoring, product separation and purification. You will test catalyst activity, lifetime and consistency using a gas / heterogeneous reactivity apparatus. In addition, you will seek opportunities to publish work, contribute to intellectual property protection and assist in commercialisation activities. This offers the opportunity to develop wider research skills and networks which could support career development either in academia or industry.

We are looking for a Research Fellow to join our team working on stochastic analysis, with a focus on regularisation by noise phenomena. The post is funded by the EPSRC project EP/Y016955/1 “Regularisation by noise: beyond Itô’s theory” and aims to investigate the effects of noise on the well-posedness and qualitative properties of solutions to differential equations, with a focus on non-Markovian and/or infinite dimensional settings.

You will work closely with Dr Konstantinos Dareiotis and Dr Khoa Lê. You will have a PhD in Mathematics (or have submitted your thesis before taking up the role) or a related discipline, and a strong background in stochastic analysis, partial differential equations, and functional analysis. The position is for two years, starting from October 2024 or as soon as possible thereafter.

We are seeking a Research Fellow in Digital Flow Chemistry to develop automated reactor platforms for screening and optimising multistep reactions and apply these to synthetic case studies based on chemoenzymatic cascades.

The overarching project aims to develop an Industry 4.0 approach to integrated catalysis for sustainable synthesis. You will develop automated multistep reactor platforms using liquid handling robotics and continuous flow technology, to enable the combination of different types of catalysis into telescoped reaction sequences. This will require integration of machine learning algorithms and dynamic profiling techniques for reaction optimisation and mapping of the design space. You will work alongside other members of the group to apply these techniques on new catalytic cascades and pharmaceutical case studies.

This is a unique opportunity to join the exciting UK academic/industry collaborative project FermoChar (Fermentation residue into engineered char-based materials for sustainable industrial applications; A pathway to NetZero), funded by the UK’s Innovation Funding (Innovate UK).

This project brings together a multidisciplinary team of expert researchers in process engineering, biotechnology, adsorbent characterisation within the School of Chemical and Process Engineering, University of Leeds, Teesside University, and associated industrial partners working in the fermentation sector.

You will contribute to the production and characterisation of carbonaceous adsorbents from hydrothermal carbonisation of fermentation residues. The overall project aim is to develop methodologies for the valorisation of fermentation residues from different biotechnology processes. The appointed researcher will specifically focus on. i) the production of novel bespoke adsorbents, (ii) modification of adsorbents, (iii) experimental screening of different activation approaches, (iv) the production of materials for adsorption testing and (v) process optimisation and design.

We are looking for a postdoctoral researcher to join our research team to investigate the benefits of plant bioactive compounds on animal productivity in a collaborative project with academic and industrial partners. The project addresses the huge wastage of plant crops that occurs at present at the farm production and processing stage, through the development of innovative and sustainable valorisation strategies that convert agri-food waste streams into next-generation feed additives to increase animal health and productivity.

In particular, you will focus on the encapsulation and targeted release of bioactives paired with functional biopolymers and work with our industrial partners on sourcing the bioactives and biopolymers as well as the scale-up of selected bioactive fractions as feed ingredients. The efficacy of the developed formulations towards improving gut health and animal health will be evaluated in subsequent feeding experiments at the National Pig Centre, University of Leeds Spen Farm. It is expected that you will contribute to the delivery of the trials and the analysis of biological samples.

The project combines different academic disciplines, including food chemistry, biopolymer and food colloids, animal production, molecular nutrition, and it comprises a consortium of several industrial and academic partners in the agri-food space.

This industry supported project “Objective and Subjective Characterisation of Textile Materials” aims to establish improved understanding of the nature of the interface interaction between the textile material and the skin. The ground-breaking approach will link textile materials insight with interface characterisation. You will work within a multi-disciplinary team of experts to carry out research about textile materials, fabric/skin characterisation and laundering and will be actively involved in research, potentially producing high quality publications and contributing to the School’s Research Excellence Framework (REF).

You will have a PhD (or near completion) in textile technology and ideally some experience in instrumental analysis technology. In addition, you are developing a record of research commensurate with the level of the post and with a clear indication of the ability to achieve internationally recognised standards of excellence. 

Funded by the Niall Community Fund we are undertaking a piece of research that will establish the kinematics and kinetics of gait and the associated muscle activity of walking. This data will then be used to further inform the development of a home-based gait rehabilitation device, principally for use by people with a spinal cord injury.  The work will involve literature/systematic reviews, cross sectional data collection in our labs, analyses of data using AI techniques, and further refinement of the rehabilitation device. 

You should have a PhD (or close to completion) in Sport and Exercise Sciences, Mechanical Engineering, or a closely allied discipline, with experience in collecting and analysing 3D kinematic data, surface electromyography, and force platform data.

The role will involve working at the cutting edge of Choice Modelling but with a keen focus on helping to build bridges across areas, helping to develop modelling frameworks that will actively shape future policy making. The successful candidate will need to demonstrate sufficient theoretical and technical knowledge in choice modelling, and possess an open mind to new ideas and approaches. Knowledge of a programming language, with an emphasis on R and/or Python, is also strongly advised. 

As a member of the team, you will be based at the Institute for Transport Studies (ITS) where you will work with Professor Stephane Hess and other researchers in the Choice Modelling Centre (CMC), drawing also on expertise in its global network. You will become part of a highly productive team, have the opportunity to work with other groups in the University of Leeds and take part in international conferences for the purpose of disseminating the findings of the research. You are expected to contribute to methodological research on bridging choice modelling, mathematical psychology and machine learning in the context of transport, health and environment. As this is a multi-faceted research project, you will be able to contribute to individual components of the work as well as helping to shape the direction of the research according to your own interests and background. You will be expected to take academic ownership of large parts of the programme and make a lasting contribution to the field.