16 Postdoctoral Fellowship at University of Manchester, England

We seek to appoint a post-doctoral research associate in turbulence modelling & simulation who is ready to contribute to world-leading research in the domain of Computational Fluid Dynamics and Turbulent Flows. The successful candidate will have completed a related PhD and will have a strong teamwork mentality and a growth mindset.

This position is focused in the domain of novel approaches for the numerical simulation of turbulent flow, including the coupling of advanced unsteady turbulence modelling with zonal scale resolving methods, via use of synthetic turbulence. The research associate will also work on extending a recently developed multi-fidelity modelling framework for industrial applications with high geometric complexity.

The successful candidate will have demonstrable expertise in the development of Computational Engineering software for fluid dynamics and turbulent flows. They should also be able to evidence extensive programming experience, the use of high-performance computing facilities, advanced data analysis skills and a track record of successful dissemination of their research via top journal papers and oral presentation at international conferences.

A postdoctoral position for 3 years is available through UKRI funding underwriting a European Horizon-EIC Pathfinder Open grant entitled QUANTUM-TOX. This postdoc is part of a European collaborative consortium, with a total funding of 3 million euros, aiming to make a step change in computational toxicology. The post is tenable from 1st March 2024.

The need for fast, cheap and accurate technologies to assess toxic effects is pressing. Computational toxicology provides an array of methods for toxicity prediction only using computer approaches. However, contemporary computational toxicology has severe limitations. Predictions typically use Quantitative Structure-Activity Relationship (QSAR) models that rely on large sets of molecular descriptors. This causes severe problems since the methodologies cannot assess chemicals different than the ones used to develop the QSAR models, This project will develop a new type of descriptor, totally based on quantum mechanics, which can cover the whole chemical space and relies on a small number of parameters that are easily interpretable.

The position is open to an outstanding and ambitious computational chemist. Based within the Department of Chemistry, you will work with Prof Popelier and his vibrant research group. The Department is ranked 3rd in Great Britain and 5th in Europe by the 2021 Nature Index.

With the nuclear industry experiencing a resurgence, The University of Manchester is committed to providing ground breaking research to aid the advancing nuclear sector. We are home to the Dalton Nuclear Institute and have strong links with industry, both in the UK and overseas, notably those with UK Atomic Energy Authority (UKAEA) and the National Nuclear Laboratory (NNL).

The UK Government has committed to building STEP (Spherical Tokamak for Energy Production), a prototype fusion power plant, by 2040, which will use lithium-6 to generate tritium for the fusion reaction. More than 100 tonnes of isotopically pure lithium-6 will be required for its operation, yet there is no large-scale lithium isotope enrichment plant in the Western world. Investment in a lithium enrichment process in the UK will ensure security of supply and open the potential to become a global exporter of enriched lithium-6.

The biggest challenge facing the implementation of this technology is its currently low technology readiness level (~TRL 1). The University of Manchester, the University of Leeds and Global Nuclear Security Partners are working as a team with funding from UKAEA to rapidly raise the TRL and demonstrate a comprehensive process to enrich lithium-6. The research focuses on bridging the gap between fundamental chemistry and process engineering by demonstrating process scale-up, online monitoring, lifecycle analysis and lifecycle costings, regulation, and product form and purity. The project embeds environmental responsibility, including a focus on waste minimisation and management, as well as the identification of areas for reducing energy consumption.

While the incidence of lung cancer in smokers is decreasing in many more economically developed countries, lung cancer incidence in non-smokers is increasing in many countries. The Sherlock-lung study (Zhang 2021) is collecting cancerous and healthy tissue from 2000 never smoking lung cancer patients and conducting multiomic analysis to elucidate the aetiology and evolutionary paths to progression in this cohort. The Wedge lab pioneered computational methods for studying tumour evolution and heterogeneity using short read, bulk whole genome sequencing (Nik-Zainal 2012, Gerstung 2020). We are now looking for a talented postdoctoral bioinformatian to further develop these methods, taking advantage of the additional information provided by PacBio HiFi sequencing.

The University of Manchester invites applications from outstanding candidates with a track research record in the area of pharmacy practice research for a position of Research Associate.  Funding is available to undertake this post on a full-time or part-time basis.

The successful applicant will join the Centre for Pharmacy Workforce Studies (CPWS) in the Division of Pharmacy and Optometry, and will work on an NHS England commissioned evaluation of the impact and learning from Independent Prescribing (IP) within Community Pharmacy (CP) Pathfinder sites. The post-holder will also be expected to work on other pharmacy workforce related projects underway within CPWS. This post will involve delivery of projects in a timely and rigorous fashion and to a strict timetable and budget. This will involve liaison with the project team and wider external collaborators.

You will have a PhD (or equivalent) in the field of pharmacy or broader health services research. You will have previous experience in qualitative research, including the use of appropriate software packages for data analysis (e.g. NVivo). You will have evidence of publishing papers in high quality peer reviewed journals.

This position is being created as result of a decision by the University’s Directorate of Social Responsibility to fund an investigation on the history of research undertaken in the early 1960s by the psychologist Dr Maurice Philip Feldman and the psychiatrist Dr Malcolm J. MacCulloch at Crumpsall Hospital, supervised by Dr Northage John de Ville Mather, a forensic psychiatrist who was Consultant Psychiatrist at North Manchester Group of Hospitals and lectured at the University of Manchester’s Department of Psychiatry, with the aim to develop a method intended to change homosexual behaviour, which these researchers termed ‘anticipatory avoidance therapy’, and which is now more commonly known as ‘conversion’ or ‘aversion therapy’. Feldman and MacCulloch joined the University of Birmingham in the academic year 1966-67, but continued to publish the results of the trials they oversaw at Crumpsall Hospital. The University of Birmingham commissioned a report on the work of Feldman and MacCulloch in 2021. Following the publication of the report on the results of this investigation, we felt that it was necessary to look at the history of the research undertaken at Crumpsall and the extent to which the University of Manchester was involved.

We invite applications for a Postdoctoral Research Associate to join our world-leading Greenhouse Gas Research team at the University of Manchester. This exciting post will involve joining a UK team to quantify emissions from greenhouse gas sources in the UK using unmanned aerial vehicles (UAVs). This will include conducting UAV survey fieldwork and the development of instrumentation and methods to achieve accurate emissions data.

Recent record-breaking global atmospheric methane growth rates have increased the challenge of meeting Net Zero targets by 2050. Large cuts in methane emissions are needed this decade to slow global temperature rise, and remediation targets need to be identified urgently. The new NERC-funded MOMENTUM (Mobile Observations and quantification of Methane Emissions to inform National Targeting, Upscaling and Mitigation) project, will conduct mobile greenhouse gas measurements to improve quantification of emissions from onshore methane sources, and identify priority mitigation targets in support of UK emissions policy. 

The MOMENTUM project will focus on the identification, characterisation, and quantification of anthropogenic methane sources in the UK. This will include a range of targets, including gas installations and leaks, landfill sites, biogas plants, wastewater treatment plants and farms, with the aim of understanding processes leading to emission and comparison with national GHG inventories The University of Manchester hosts a UAV greenhouse gas laboratory, equipped with rotary and VTOL drones and state-of-the-art spectroscopic instrumentation for precision measurement of GHG concentrations and micrometerology.

We invite applications for the position of Post-Doctoral Research Associate to join the team on a 5 year, £3.2M, NERC Large Grant  “Feedbacks between mineral reactions and mantle convection”, a project to shed new light on how mineral reactions influence the positions of major seismic discontinuities in Earth’s mantle. Key hypotheses to be explored are: the “dynamic pressure” in the mantle has an effect on mineral reaction and hence the positions of seismic discontinuities, and that stress has a major effect on reaction conditions and again on the positions of seismic discontinuities.

Your role will have two main focuses. The first will be to perform new experiments at mantle conditions (up to 25 GPa, temperatures up to 1800°C) measuring the effect of stress on evolving mineral properties. To understand how the minerals change, we will examine the experimental products to discover the details of structure and chemistry on the scale of individual grains. The second focus is to commission and perform the first experiments on a new high-pressure deformation apparatus. This new apparatus is an upscaled version of the DT-Cup, multi-anvil apparatus (Hunt et al., 2014, 2019, Hunt & Dobson 2017) and is designed to be capable of controlled strain-rate deformation experiments at lower-mantle pressures (>23.5 GPa). With this you will deform samples under controlled stress conditions.

The Robotics for Extreme Environments Group invites applications for a postdoctoral research position to develop reinforcement learning techniques that will improve the performance and reliability of robotic systems deployed into extreme environments. The successful candidate will work at the RAICo One facility in Cumbria, where they will have the opportunity to work in close partnership with robotics experts from the University of Manchester, Sellafield Ltd and the UK Atomic Energy Authority.

The performance of reinforcement learning when applied to robotic systems is still limited, particularly in relation to the reliability and mission success rates. A major issue is the need to manually design the reward function for each robotic problem, which requires the designer to be knowledgeable and skilled in the field, as well as relying on an inefficient trial and error methodology. This often leads to suboptimal behaviors, such as robots becoming stuck in suboptimal rewards or repeatedly performing the same action.

This project aims to reduce the reliance on the manual design of reward functions when using reinforcement learning in robotics. It is expected that this will be achieved using learning through demonstration, as well as exploration strategies. However, the successful candidate will also be expected to follow their own ideas to help address this challenge, with the end goal to develop an approach that can be used in a range of robotic problems with minimal effort. The developed approaches will be deployed and tested throughout the research programme using a range of robotic systems, including AgileX and Clearpath mobile robot platforms, Boston Dynamics and Unitree quadrupeds and Kinova and Kuka manipulators. Demonstrations will be made to industry collaborators using mock-ups of extreme environments, including realistic simulations of nuclear decommissioning facilities.

The University of Manchester invites applications to join a new research team formed to undertake research into post-qualification pharmacy workforce education and training. The post will be available immediately and will be tenable until 31 March 2026 in the first instance. Funding is available to undertake this post on a full-time or part-time basis.

Applications are welcomed for a full-time Research Associate to carry out research for the ‘Making Change Meaningful for Adult Male Prisoner Survivors of Sexual Assault Project’.

The Project is funded by The University of Manchester and the post is based in the department of Criminology, in the School of Social Sciences, The University of Manchester.

The role will involve online in-depth interviewing with male victims of sexual assault who are currently serving custodial sentences. It will also involve the preparation of transcriptions of these interviews and the collation of psychometric data shared by the NGO, We Are Survivors.

The project will by directed by Professor David Gadd in the Department of Criminology, School of Social Sciences at The University of Manchester (UoM).

The Postdoctoral Research Associate (PDRA) will be responsible for developing computer codes to simulate Pressure and Temperature Swing Adsorption processes for carbon capture applications. The Sarkisov group at Manchester is a leading group in the multiscale screening of porous materials for various applications, including carbon capture. In this multiscale workflow, data is initially generated at the molecular level through molecular simulations.

Subsequently, this data is integrated into the process level to analyse the behaviour of promising adsorbents in realistic process modelling. The PDRA will need to develop computationally efficient algorithms for the process modelling stage and explore the potential acceleration of these algorithms using Machine Learning (ML) methods.

We are seeking to recruit a Research Associate to undertake research and project management duties for the UK Energy Demand Research Centre (EDRC). The appointee will be in charge of ensuring that the project is progressing in line with anticipated schedules and deliverables, while liaising with relevant partners and stakeholders. The Research Associate will undertake, in the main, qualitative data collection and analysis (desk-based document collection, interviews, ethnographies, governance mapping, social network analysis) on issues of energy demand, retrofit and employment across the UK. The post holder will also be tasked with preparing and writing project reports, peer-reviewed publications and follow-on funding applications, in addition to undertaking non-academic dissemination activities linked to the project.

We are looking to recruit additional Post Doctoral Research Associates (Grade 6) to join our interdisciplinary Future BRH team who are working on a mix of industrial biotechnology and biomanufacturing projects. These new research positions are available to fit within the FutureBRH research portfolio Grand Challenge research themes “Automated and integrated biocatalyst engineering for biomanufacturing” and “Realising the value of industrial biotechnology at scale”. Specific projects will focus on: Yeast strain engineering; Sophorolipid  production; Industrial host strain engineering and Responsible Research and Innovation (RRI). You will be based in the Manchester Institute of Biotechnology (MIB) which is a cross-disciplinary research centre and part of the University of Manchester (UoM).

We are committed to creating a fully inclusive and flexible culture, one where everyone can realise their potential and make a positive contribution to our organisation. We believe that if we can positively diversify our staff we will be able to collaborate more effectively and create a more productive environment.

The University of Manchester has a vacancy for an experienced Research Associate / Research Fellow, to manage (under supervision) a clinical trial which forms the key work package of the prestigious NIHR Programme Grant entitled “Prevention of Suicide in Prisons: Enhancing Access to Therapy” (PROSPECT). The primary objective of the PROSPECT project is to improve, and subsequently evaluate, access to a psychological therapy programme for prisoners identified to be at risk of suicide (Chief Investigator: Dr Daniel Pratt).

The Research Associate / Research Fellow will support the Chief Investigator (CI), Principal Investigators, and other researchers and clinicians to ensure trial governance, smooth running and successful completion of the PROSPECT trial. You will be responsible for all trial management activities for the trial and ensure efficient and successful completion.

The post requires expertise and experience of health services research (project management, literature reviews, data analysis) and a strong understanding of both qualitative and quantitative methodologies. You will be a talented, self-motivated independent researcher with drive, enthusiasm and excellent communication skills, with the ability to manage a trial through to a successful completion. You will have excellent written, verbal and numeracy skills and a strong ability to work independently and as part of a team. You will manage the day-to-day running of the trial and the delivery of key milestones and objectives. You will have excellent organisational skills for the coordination of a complex multisite trial and the ability to manage parallel tasks with tight deadlines. It is essential for the successful candidate to have a creative approach to problem-solving and to have the ability to assist with the direction of the work of a small team of research assistants and motivate others to produce a high standard of work.

Applicants are invited for the post of Postdoctoral Research Associate at the interface between probabilistic machine learning and sustainability.

You will join a team of probabilistic modellers and machine learning researchers developing new collaborative AI principles and methods. This is an exciting topic which inspires new problems in fundamental ML work, and allows attacking new applications which make a difference, for instance in scientific research. Different team members have different expertise, and by working together are able to address more novel problems. Keywords include automatic experimental design, Bayesian inference, human-in-the-loop learning, machine teaching, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, computational rationality and user modelling, and simulator-based inference. These probabilistic models will be used to improve sustainability in a collaboration with the Sustainable Materials Innovation Hub, using – for the first time – sustainability inputs to direct outcomes. Prior experience in sustainability or life cycle assessment is a plus but not required.

The team is funded by a collaborative Horizon Europe project and is jointly hosted in the recently established Centre for AI Fundamentals and Sustainable Materials Innovation Hub. These cross-Faculty initiatives sit at the interface between university’s excellence in AI and environmental sustainability research and innovation.