24 Postdoctoral Fellowship at University of Manchester, England

Opioid utilisation for non-cancer pain and related adverse outcomes have reached epidemic proportions in the US, Canada with rising trends in the UK 1-4. Opioids have led to a major societal burden in North America; however, less is known about their utilisation in vulnerable subgroups and safety in Europe and the UK. Some opioid users may be particularly vulnerable to related harms due to specific individual factors such as older age, specific comorbidities and polypharmacy. Maximising benefits and limiting risks of treatment for such patients is therefore a national public health priority. We will use state of art statistical models and novel study designs to evaluate the comparative safety of opioids in relation to short term and long-term safety outcomes. The programme of work will move risk estimation towards personalised risk, whereby patients can be informed of their individual risk of side effects before starting the drug. Although focussed on opioids, the skills and methods developed will have wider application for investigating the safety of other medications.

This position is for research within RAICo1, a joint initiative developed by Sellafield Ltd and the Nuclear Decommissioning Authority (NDA) in collaboration with the UK Atomic Energy Authority (UKAEA), The University of Manchester, and the National Nuclear Laboratory. In Whitehaven, West Cumbria, RAICo1 is the first of a network of robotics and artificial intelligence hubs across the UK. Size reduction of existing radioactive waste is paramount for its relocation and safe storage in modern nuclear facilities. Due to the intrinsic hazard of such handled materials, robots are usually employed to move humans away from harm. Nonetheless, cutting material into smaller parts is usually time and labour-intensive. It requires engineers to define the sequence of cutting paths, program the robot to execute that sequence, and manually update the CAD models of the material being cut. This project will develop an automatic planner to generate the cutting sequence and the collision-free paths, enabling fixed-base manipulator robots to laser cut skips (containers) with minimum human intervention, reduced time, and increased reliability and flexibility. The outcomes of this research will be a stepping stone for future developments of fully autonomous robots for remote handling and size reduction.

An exciting opportunity has arisen for a Research Associate in Data Science and Analysis working on long-term pharmacovigilance registers for adults with rheumatoid arthritis (RA) and children and young people with arthritis (Juvenile Idiopathic Arthritis) who are being treated with advanced therapies. The Biologic Studies Group (BSG) has over 20 years’ experience of hosting some of the largest real-world biologic observational studies in the world and is viewed as the gold standard for this type of data capture in rheumatology. The data are also being expanded through linkage of the datasets to other validated national healthcare data resources, such as those held by NHS Digital including Hospital We need a researcher who understands working with large datasets, including cleaning, data wrangling, and analysis of data, who has an excellent eye for detail and who can present and publish their findings at conferences and in journals. Day to day you will generate standard reports for the funders, as well as working on your own research analyses. You will be able to make a major contribution to this important area whilst extending your own experience, research skills and building your CV. You will assist study staff, students and external stakeholders working on the data. Excellent communication skills are required to effectively tailor and convey information to these groups including lay audiences where required.

The post-holder will join a team of computational, mathematical and experimental biologists funded by a Wellcome Trust Discovery Award “Defining the spatiotemporal gene expression dynamics controlling embryonic patterning”. They will be responsible for developing and refining systems biology models of drosophila embryogenesis. This will include developing both stochastic models of high-resolution live cell imaging from individual genes (e.g. modelling transcription and translation processes) and spatio-temporal modelling of gene regulatory networks involving hundreds of genes. The project will require the integration of in-house and public datasets along with incorporating/adapting published gene regulatory network models for early embryogenesis. As well as developing models from the data, they will be required to carefully consider appropriate pre-processing, normalisation and signal processing, as these steps can be of critical importance for developing models from imaging and omics datasets. They will work with the rest of the team to improve and refine models through data-driven inference approaches. Models developed will be used to gain mechanistic insights and design/interpret perturbation experiments that will feed back to improve the model.

The post-holder will join a team of computational, mathematical and experimental biologists funded by a Wellcome Trust Discovery Award “Defining the spatiotemporal gene expression dynamics controlling embryonic patterning”. They will be responsible for developing and applying probabilistic machine learning methods for modelling high-resolution spatio-temporal data (e.g. live cell imaging and spatial transcriptomics) collected during embryonic development. We are applying a range of methods, including but not limited to Gaussian process modelling, hidden Markov models and deep learning approaches. One promising approach that we would like to explore is the development of latent force models that can capture the spatio-temporal developmental dynamics, integrating gene regulatory network modelling with Gaussian process inference. We are generally interested in approaches that combine data-driven modelling (machine learning) with mechanistic modelling (systems biology). Models developed will be used to gain mechanistic insights and design/interpret perturbation experiments that will then feed back to further improve the model.

You will join a growing team to support an industrial research project in volumetric SAR imaging, understanding how iterative reconstruction techniques perform (and can be improved) to work with realistic SAR data, and undertaking further research and development into regularisation of complex-valued imagery and computational methods for nuisance parameters and auto-focusing. Through implementing new methods in the CCPi Core Imaging Library, supported by research software engineers, you will help project partners QinetiQ and the Defence Science and Technology Laboratory (DSTL) understand how computational inverse problems methods could be transitioned into practical use for SAR.  You will work with a wide range of researchers, collaborators and stakeholders, across multiple organisations and from different disciplines, employing and developing your skills in knowledge transfer.  You will also need to contribute to project reports and milestones, ensuring you develop research goals which can be met within the project timelines.

This is an exciting opportunity to work on a qualitative healthcare project about writing outpatient clinic letters directly to patients. The work is likely to have a significant impact on national practice within the rheumatology community and beyond.  The successful applicant for this post will be engaged in, and have experience of;  liaising with PPIE contributors, applying for ethics, recruitment and selection of participants, conducting the research, preparation of papers and presentations of findings.  The research will include surveys, interviews, focus groups and workshops with rheumatology patients and the multi-disciplinary team. The applicant will be required to conduct interviews at times and in places suitable for participants and will be expected to liaise regularly with the Principal Investigator and the wider co-investigator team. Use of NVivo will support thematic analysis and organisation of findings. The successful candidate will also be expected to conduct workshops and work with stakeholders to co-produce resources to support the multi-disciplinary team to write directly to patients.

We are seeking to appoint a Research Associate to work in the Jodrell Bank Centre for Astrophysics in the group of Prof. Lucio Piccirillo to study the noise generation mechanisms in High Electron Mobility Transistors. The candidate should have a solid understanding of the working of HEMT transistors and low noise amplifiers, cryogenic techniques and fabrication processes including but not limited to photolithography, laser writing, etching, sputtering, evaporation and SEM. Working knowledge of HFSS, ADS and mechanical CAD are desirable. The Department of Physics and Astronomy is committed to promoting Equality, Diversity, Inclusion and Access through contributing to the University’s social responsibility agenda, demonstrating a commitment to its policies, activities and delivery of initiatives including the Athena SWAN charter for promoting women’s careers in STEMM subjects (science, technology, engineering, mathematics and medicine) in higher education. The Department has held JUNO Champion status since 2016 for its commitment to achieving gender equality which positively promotes inclusivity for all.

The successful applicant is expected to have a PhD or equivalent in physics, electronics, materials science or nanotechnology. Expertise in 2D materials transfer and device fabrication in a clean-room setting is essential. You should be capable of working under your own initiative and help manage a small research team, so excellent communication and organisation skills are also required. The successful applicant will design and fabricate spintronic devices based on 2D materials heterostructures, combining 2D materials with spin-orbit coupling and room-temperature 2D ferromagnets, to develop an experimental prototype memory device based on the spin-orbit torque (SOT) mechanism. You will work predominantly in the clean rooms of the National Graphene Institute and in the Condensed Matter Physics Group laboratory in the Department of Physics and Astronomy. The work will be developed within a Horizon Europe collaborative project.

An EPSRC-funded Postdoctoral Research Associate position with Prof Nikolas Kaltsoyannis is available for 36 months from 1/2/24, and will involve the computational quantum chemical study of bimetallic homogeneous catalysts for the conversion of nitrogen to ammonia, and secondary or tertiary amines. The project is a collaboration with the synthetic inorganic chemistry team of Prof Polly Arnold, FRS, in the Department of Chemistry at the University of California at Berkeley, USA. An outstanding and ambitious computational chemist is required, who should be capable of working under their own initiative and within a research team, so excellent communication and organisational skills are required. Applicants should have, or be about to obtain, a PhD in molecular computational quantum chemistry. To maximise the benefits of the experimental-computational collaboration, the PDRA will spend up to 6 weeks per year in Berkeley, for each of the three years, working closely with Arnold’s team.

The UK has been generating electricity from nuclear power for over sixty years. Nuclear power generates 15% of the UK’s electricity as of 2023, and current government plans call for this percentage to rise to ~25% by 2050. Consequently, the issue of safely disposing of the UK’s existing ~750,000 m3 Intermediate and High-Level Waste (ILW/HLW) and future waste is a clear priority. The UK government policy is to dispose of the higher activity wastes in an underground geologic disposal facility (GDF) at an estimated cost of £20-53 billion over a multi-decadal lifetime. One of the rock types identified as a potentially suitable host rock for the siting of a GDF are lower strength sedimentary rocks (LSSRs). The purpose of a GDF is the safe disposal of radioactive waste for periods of tens of thousands of years, in a manner that ensures that any transport of radioactive materials into the surrounding biosphere is kept below specified limits. Siting and construction of a GDF in LSSR will therefore require a quantitative understanding of both the physical and (biogeo)chemical properties of the host rocks surrounding a GDF. However, many fundamental gaps still exist in our knowledge of the issues related to performance of these host rocks as a geological barrier to radionuclide transport. Addressing these gaps requires fundamental new understanding which will require development and application of the next generation of experimental, analytical, and modelling approaches to meet the challenges of characterising key processes in these complex systems.

We are looking for academics of outstanding ability, who are seeking a friendly, supportive and collegial environment in which to develop as world-class researchers, and who will contribute to the continued development of the Probavbility & Statistics Group, Department of Mathematics, in the School of Natural Sciences.

We are seeking an individual with a strong background in protein structural biology, biophysics or biochemistry.  You should have a PhD (or be close to completion) in Biological Sciences, Structural Biology, Biophysics, Biochemistry or a closely allied discipline. Previous experience in EPR (pulse and/or CW) spectroscopy or structural mass spectrometry (HDX and/or native) is highly desirable. Experience in cloning, protein expression and purification would also be desirable for this project.

 

(18) Postdoctoral Fellowship Position

Postdoc Fellowship Position summary/title: Research Associate in Data Science

Deadline : 14/11/2023

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We are looking for an individual who has interest in and knowledge about issues involved in providing paediatric hearing health care and has an awareness of research in this area.  The candidate should have experience of conducting qualitative research. The candidate should be organised, self-motivated, and passionate about working with diverse communities to ensure all have equal and fair participation in the JLA process. This is an ideal opportunity for an individual seeking post-doc experience or for someone with specialist skills in providing hearing health care and/or working with diverse communities including children and young people, collecting and analysing qualitative datasets, and using systematic techniques to review existing scientific literature.

Working under the umbrella of the Centre of Applied Pharmacokinetic Research (CAPKR) group, you will be fully involved in a CAPKR-funded project entitled ‘Liquid Biopsy and Endogenous Biomarkers to enhance or replace specific DDI studies in Patient Populations’. You will hold a PhD in a biomedical, pharmaceutical or systems modelling research area, and have a background in determining activities of drug metabolizing enzymes and/or transporters using different in vitro systems and experience in physiologically-based pharmacokinetic (PBPK) modelling incorporating in vitro-in vivo extrapolation. Emphasis will be placed on a developing publication record.

The aim of the project is to develop new and improved 1D, 2D and 3D NMR methods to address some of the most challenging problems in the field of mixture analysis. In many areas (e.g. chemical process development, quality control, food science, metabolomics) the majority of the samples of interest are heterogeneous mixtures, and here NMR plays a pivotal role due to its non-destructive and quantitative nature. These often have very broad and crowded NMR spectra, due to the presence of many species with many different concentrations, and the spectra are therefore very difficult (sometimes impossible) to interpret. The project will focus on exploring novel strategies for obtaining clean and high-resolution NMR spectra, in order to allow the identification, quantification and structure determination of all components in mixtures. The project will involve experimental work using a range of spectrometers, with most work carried out on Bruker NEO 500, Bruker NEO 700, Bruker AV III 500, Varian/Agilent VNMRS 500, and Bruker AV III 400 spectrometers (with access to Bruker AVANCE III 400, 500, 600 and 800 instruments, and to cryogenic probes, as necessary); computer programming, mostly in C and Matlab, for data processing; and theoretical analysis, supported by simulation using Matlab and Mathematica.

Survey Futures is a collaboration between nine universities and three survey organisations, in partnership with the National Centre for Research Methods (NCRM) and the Office for National Statistics (ONS). Its objective is to deliver a step-change in survey research to ensure that it will remain possible in the UK to carry out high-quality social surveys of the kinds required by the public and academic sectors. The post is based in the Social Statistics Department, School of Social Sciences, University of Manchester, and will involve working on methodological research and theoretical development for Survey Futures, together with the University of Manchester investigators, Dr Alexandru Cernat and Professor Natalie Shlomo, in collaboration with partners across participating organisations. The Director is Professor Peter Lynn of ISER, the University of Essex and the Deputy Director is Dr Olga Maslovskaya, University of Southampton. The appointment will be funded for 30 months. Survey Futures aims to assess the quality implications of the most important survey design choices relevant to future UK social surveys, to provide good practice guidance and practical training materials, and to identify promising ways to improve the capacity and skillset of both interviewers and research professionals.

The University welcomes applications for applied electronics research engineers within the School of Engineering. The post has become available due to recent extension of bioelectronics activities in the Department of Electrical & Electronic Engineering over three interrelated topic areas covering intelligent sensor systems research for delivering next generation crops and arable farming technologies. Working in partnership with industrial as well as academic researchers from other institutions and universities, the successful applicant(s) will become part of a multidisciplinary team notably in collaboration with plant scientist, materials engineers and business development researchers. Applications are particularly welcomed from individuals who have interests in a longer-term research career in intelligent sensor systems and bioelectronics. Support will be provided to such applicants in their downstream application to Fellowship schemes or obtaining any further qualifications, such as chartered engineering status or a higher degree / PhD (if appropriate), to extend the successful applicant’s career.

Applications are invited for a Research Associate/Fellow position in the Department of Electrical and Electronic Engineering at the University of Manchester. The purpose of the job is to develop high-speed imaging systems for the next generation of atmospheric monitoring systems. This is a 2.5-year fixed term position, with possible extension subject to funding. We are looking for a digital system designer, capable of developing bespoke high-speed interfacing and signal processing systems, using high-end FPGA devices and custom silicon circuits. Experience in high-level system modelling as well as solid knowledge of RTL is required. Experience in mixed-signal design and backend VLSI chip implementation would be advantageous. The post is suitable for candidates with a PhD in Electronics, or a related discipline. Candidates with equivalent industrial experience are welcome to apply. Candidates with significant experience will be considered for appointment at a Research Fellow grade. Please use the link below for full job description and further particulars