Duties: The School of Medicine, Dentistry and Biomedical Sciences is currently seeking to appoint an exceptional candidate to the post of Lecturer in Bioinformatics to undertake research in the Patrick G Johnston Centre for Cancer Research and the School of Medicine, Dentistry and Biomedical Sciences at Queen’s University Belfast (QUB). The successful candidate will develop a bioinformatics research theme in line with the School/Centre’s research strategies, teach at undergraduate and postgraduate level and contribute to the School’s administration/outreach activity
Requirements: Primary or higher degree in a life sciences, mathematics, programming or a cognate subject; PhD in a biomedical science, biology, or a related discipline to bioinformatics; A minimum of three years’ recent experience in discipline(s) related to bioinformatics; Experience of use of the R statistical environment; python or similar higher-level scripting/programming techniques; Recent, relevant publications in peer reviewed/refereed journals that are high quality and are commensurate with stage of career; Experience of working in collaborative research projects

Duties: Develop new mathematical methods for sensitivity analysis, Implement computationally efficient numerical methods suitable for large-scale flow simulation and Validate the approach by designing novel structured surfaces for wall-bounded flows. In addition, you will take part in collaborative work with the project partners, take part in and contribute to the research group's activities, publish new findings in peer-reviewed literature and disseminate results at national and international conferences. There will also be an opportunity to gain experience in teaching and student supervision
Requirements: To be successful, you must have a PhD or equivalent professional qualification in Fluid Mechanics, Applied Maths, Computational Sciences or a related subject. In addition, you should demonstrate expertise in developing mathematical/computational methods for analysis, modelling or simulation of fluid flows. It is essential you have good analytical skills. Proficiency in computing and/or numerical simulation of fluid flows is highly desirable

Department: Medical Physics and Biomedical Engineering - Photoacoustic Imaging Group
Workload: 100%
Duties: Applications are invited for a research fellow position to work on the development of a near infrared and shortwave infrared fluorescence imaging scanner applied to cancer. The scanner will be used to image antibody-conjugated dyes to improve the accuracy of fluorescence-guided surgery of paediatric solid cancer. The goal is to translate the findings to a human clinical trial and the job maybe extended accordingly subject to further funding. The scanner will be combined with an all-optical photoacoustic imaging scanner to create a dual modality intraoperative imaging system to better detect cancer cells that remain during surgical removal and to improve the visualisation of vital organs and vessels
Requirements: An engineer or physicist with strong applied optical engineering skills is sought. Candidates must have a PhD in a relevant subject or equivalent qualifications and/or work experience. Practical experience in the development of fluorescence spectroscopy or fluorescence imaging systems for biomedical applications is essential. The project is funded by a Wellcome Trust Innovator Award (PI: Mr Stefano Giuliani) and it will be carried out in collaboration with research groups at the UCL Great Ormond Street (GOS) Institute of Child Health, the Institute of Cancer Research (Marsden), and the Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) at UCL; Therefore, enthusiasm in the project, good inter-personal skills and experience of interdisciplinary working are essential. Knowledge of, or a wider interest in, Biomedical optics or Photoacoustics, is advantageous but not essential

Department: Division of Psychology and Language Science
Workload: 100%
Duties: In this new study, we will develop a novel preventative intervention, delivered in the school setting, which integrates targeted training in emotional processing with group interpersonal therapy (IPT) that addresses young people’s social relationships. Given the rapid rise in mental health difficulties that occurs in early to mid-adolescence, the study focuses on ages 13-14 years (school years 8 and 9), which represent an ideal phase for effective prevention. This new hybrid intervention will be created through an interdisciplinary partnership between young people, teachers, psychologists, sociologists, parents, clinicians, statisticians, digital health experts and performing artists
Requirements: We are looking for an individual with excellent skills in multivariate statistics and scientific writing. The ideal candidate will also have experience in conducting research with young people and have experience in longitudinal mental health/social relationships research and/or intervention studies. Experience in social network analyses would be an advantage but is not an absolute requirement for the job. The applicant also needs to possess good interpersonal skills for communicating with the wider project team

Department: Institute of Ophthalmology
Workload: 100%
Duties: This exciting position is based at the Institute of Ophthalmology, a world leading research institute focusing on vision and diseases of the eye, working with UCL’s Research Software Development Group in the Centre for Advanced Research Computing (ARC), a large and innovative group of research software engineers. You will lead on the further development of software tools and models of the metabolism of the back of the eye, with application to understanding (and treating) the effects of aging on vision. This will include rapidly assimilating knowledge of the underlying research disciplines, contributing to publications and future grant applications, and crafting sustainable, reusable software
Requirements: A strong candidate will hold a PhD or equivalent and have substantial experience in the development and coding of computational models, ideally in the context of biological systems. The existing code base to be developed is in Matlab and experience of Matlab is beneficial. It is likely that, moving forward, code will be developed in Julia. Experience of Python and/or Julia would thus be an advantage as would understanding of any relevant area of biology or physics. This would include reaction kinetics, thermodynamics, diffusion, metabolism and metabolic networks, etc. It is also expected that the post-holder will have a solid foundation in mathematics. Whilst an appreciation of the eye and vision would be helpful it is by no means required

Department: Institute of Health Informatics
Workload: 100%
Duties: Conducting analysis mainly using population level data from the BHF Data Science Centre Covid Impact project led through HDR-UK but also working with other Electronic Health Record data (Primary care data including The Health Improvement Network (THIN) and Clinical Practice Research Data (CPRD), Hospital Even Statistics (HES) and Office for National Statistics (ONS) from the CALIBER resource); Contributing as a author on a number of high impact peer-reviewed research publications in general readership clinical, genetic or science journals; Preparing for weekly in-house meetings, and national and international conferences; Representing the group at fortnightly BHF Data Science Consortium meetings and other relevant schedule calls; Contributing to the development of grant applications and manuscripts in collaboration with others in the Institute
Requirements: You have the knowledge of epidemiological and statistical methods such as Cox Proportional hazards models, trial emulation, Mendelian randomization and a good understanding of the complexities of manipulating large datatsets; You have a MSc in statistics/epidemiology/computer science/health data science/other relevant discipline or a similar level of experience; You have excellent skills in at least one statistical software package (e.g. R, STATA)

Department: Chemical Engineering
Duties: Develop a programme of original research and produce publications, as well as other research outputs, in the broad area of manufacturing related engineering; Deliver multidisciplinary research and teaching activities that support UCL priorities; Secure research grant funding in accordance with UCL Financial Regulations and the conditions of funding bodies; Recruit, manage and lead researchers; Ensure that research outputs are recorded, analysed and written up in a timely fashion and to deadlines; Report to funding bodies and others as needed; Submit papers to relevant journals and present at relevant conferences; Lead and assist with curriculum development, including learning materials and schemes of work; Keep accurate student records on progress, achievement and attendance; Teach at undergraduate and postgraduate level, including laboratory supervision, lectures and tutorials
Requirements: Lead on the development of research promoting a holistic approach to manufacturing engineering related to functional materials/chemicals/pharmaceuticals manufacturing and/or high throughput materials chemistry, and/or data science/applied statistics/machine learning/automation/digital twins/model-based design of experiments, and/or process systems engineering; Carry out and publish high-quality world-class research which complements the existing departmental and Faculty activities, and secure research grant funding to support your research programme; Support research staff and PhD students; Contribute to teaching existing or new taught modules in the areas relevant to the post

Workload: 100%
Duties: In this PhD project, you will develop a general graph-based framework to (a) facilitate efficient multi-agent communication, (b) enable learning using sparse rewards (i.e. feedback signals that are non-zero only when a goal is achieved), and (c) build a relational representation of the environment. You will be joining a larger research team based at WMG (Warwick Manufacturing Group) at the University of Warwick working on various deep reinforcement learning problems and will support the development of an open-source library of multi-agent tasks with strong connections to industry
Requirements: Candidates should have an MSc in Statistics, Computer Science, Engineering or similar quantitative background and very strong and demonstrable programming skills especially in Python

Duties: This research is part of the SPHERE Interdisciplinary Research Collaboration, which has been developing a sensor platform for the home to diagnose and help manage health and wellbeing conditions since October 2013. Some of the tasks will be: feature detection and tracking; statistical modelling and analysis; applying machine learning and deep learning methodologies; the use of one or more cameras (as well as other sensor modalities), including methods for action recognition and activity analysis; tracking and identifying across multiple rooms
Requirements: PhD in Video Understanding or Multimodal Computer Vision; Prior degree in computer science or mathematics; Detailed knowledge of video understanding state-of-the-art, approaches, datasets and problems; Experience in handling video data, for learning and inference; Experience in modelling deep learning approaches for Video Understanding; Experience and evidence of publishing at high-calibre conferences and journals; Experience in working within a multidisciplinary or cross-disciplinary team; Excellent programming skills (Python); Proficiency in deep learning frameworks (PyTorch); Good publication record in computer vision and/or machine learning; Possess excellent speaking and writing skills in English

Duties: Tutoring in Mathematics, Statistics, Computer Science, Physics, Engineering, Chemistry, Biology, Languages & TOEFL, Economics, Calculator Technical Assistance, GMAT & SAT, Others; you pay 150 CHF, Euro or US$ for your advert to appear on www.acad.jobs/Tutoring for one year. For an additional cost of 200 CHF, Euro or US$, your listing will appear in the "Featured Tutors" section on the main page of www.acad.jobs/Tutoring. Banner: Annual cost is 500 US$ per 20 % call probability at www.acad.jobs/Tutoring
Requirements: Degree or student or other experience in Mathematics, Statistics, Computer Science, Physics, Engineering, Chemistry, Biology, Languages & TOEFL, Economics

Duties: We are looking for two postdoctoral research associates to join a collaborative team working on developing new tools for real-time mathematical modelling and inverse problems at scale. These posts will contribute to two exciting projects at the intersection of data science and scientific computing focusing in the area of randomised algorithms for data sketching in aid of (i) online machine learning for human behaviour modelling in an assisted living context, and (ii) real-time inference for inverse problems associate with data analytics in manufacturing applications. The posts will be a part of the real-time simulation and computational imaging lab, within the Institute for Digital Communications (IDCOM) at the University of Edinburgh
Requirements: The right individuals are highly motivated and self-directed researchers with excellent research skills who can work independently and contribute as part of a broad multidisciplinary team, possessing experience in some of the following areas: mathematical modelling (numerical simulation of PDEs), inverse problems, statistical computing, image processing, machine learning, and model order reduction

Duties: Perform large-scale simulations (Direct Numerical Simulations) of turbulent hydrogen flames using numerical grids with tens of billions of points on supercomputers with up to two hundred thousand processors; Analyse results to develop simplified models for the simulation of hydrogen flames to be used in Large Eddy Simulation (LES) and Reynolds Average Navier-Stokes (RANS) approaches; Use data from large-scale simulations to design and train Machine Learning models; Implement traditional and machine learning models in the open source CFD suite OpenFoam and assessment of model performance
Requirements: Minimum entry qualification - an Honours degree at 2: 1 or above (or International equivalent) in a relevant science or engineering discipline. The candidate should have a master’s degree in either Physics, Mathematics, or Engineering. Competencies and/or experience in computational fluid mechanics, machine learning, computational science, and simulation software (e.g., OpenFOAM) will be positively considered, but are not essential

Duties: Work with business actuaries and underwriting teams to deliver advanced Bayesian models (utilising probabilistic programming techniques) that form the basis for rating tools and support business decisions; Research and develop cutting-edge algorithmic techniques to deliver transformational improvements in process and data quality through use of data science and technology; Work collaboratively with underwriters, actuaries, and management at all stages of the model development process; Develop scalable approaches and data science tooling that can be applied across AIG’s product portfolio; Take ownership of projects and manage junior resources; Train and support other actuarial team members in the use of advanced actuarial, modelling and data science approaches
Requirements: Experienced with use of Bayesian modelling techniques and probabilistic programming packages (Stan, Pymc or similar); At least five years of relevant data science, actuarial or predictive modelling experience; Degree in mathematics related discipline; Strong analytical and problem solving skills; Very comfortable coding in R, Python or other language popular for data science; Familiar with full stack (Linux, Docker, web servers, front end tech, CI/CD tooling); Expertise in Excel, SQL, VBA, JavaScript or other programming languages will be useful; Strong business, collaboration and time management skills, responsive to service needs and operational demands; Excellent communication, presentation, and interpersonal skills

Duties: The post will be based in the Mathematics Institute at the University of Warwick, but will involve close collaboration with Laurette Tuckerman at ESPCI Paris. You will undertake research as part of the Simons Foundation grant “revisiting the turbulence problem using statistical mechanics”. This will involve understanding fundamental and aspects of turbulence in wall-bounded shear flows through direct numerical simulation, analysis and modelling
Requirements: PhD or equivalent in Mathematics or physical science; Ability to initiate, develop and deliver high quality research and to publish in peer reviewed journals; Evidence of quality research output from experienced candidates or strong research potential from less experienced candidates

Duties: The proposed project plans to identify a NODAT ‘signature’ that will help identify individuals at higher-risk of developing NODAT, which will improve kidney transplant success rates and patient outcomes. This research proposal brings together multidisciplinary and synergistic research groups to advance our knowledge of the molecular determinants of NODAT, identify potential molecular targets, and facilitate clinical prediction. This project will provide excellent experience for a dedicated post-doctoral research fellow in a broad range of techniques. The post may involve generating new molecular data, bioinformatic analysis of data, integrating datasets, preparing regular summary reports, and taking the lead writing academic outputs and research dissemination
Requirements: Have or about to obtain PhD in relevant discipline; At least 3 years’ relevant research experience; Experience handling biological samples to generate genomic, epigenomic and/or transcriptomic data; Experience working with multi-omic data, and/or statistics for molecular biology, and/or molecular bioinformatics or other fields relevant to the post; Demonstrated experience of research methods and techniques pertinent to molecular epidemiology, longitudinal studies, and/or public health research using a range of methodologies; Experience of using data analysis packages such as SPSS or Partek; Experience of project management, delivering research outcomes, and proven ability to work in a multi-disciplinary environment as part of a research team; A publication track record commensurate with the stage of career

Duties: Help define workplans for specific Hartree Centre projects, in collaboration with business developments personnel and client subject matter experts; Identify appropriate technologies and design appropriate technology solutions; Learn and apply data centric, analytics and AI technologies; Look at validation of conclusions, and presentation of results to customers (including advanced visualisation); Make site visits to commercial and academic partners; Publish non-confidential results to build Hartree and your own profiles in the community; Contacts and Communication; Contribute to specific projects with industrial clients as needed
Requirements: Degree in a mathematical, scientific, or computer science discipline; Experience of data analysis, utilizing a range of compiled and scripting languages; Experience applying mathematics and statistics; Demonstrable ability to master new tools and technologies

Duration: 2 y       
Workload: 100%
Duties: In this project, you will analyse newly generated single cell (scRNA-Seq and scATAC-Seq) as well as novel and spatial transcriptomics data sets (In Situ Sequencing and 10x Visium) to understand the molecular properties of immune cells infiltrating tumour sites. The underlying data sets comprise thousands of unique molecular signals measured for tens of thousands of cells or physical locations in each tumour. You will employ methods from high dimensional and spatial statistics, and machine learning, to chart and understand the nature of different tumour-associated immune cells, how they interact and change biological functions and how the underlying molecular changes could be exploited as therapeutic targets
Requirements: You will have a PhD in Bioinformatics, Computational Biology, Biostatistics or in a related quantitative field (e.g. Mathematics, Physics, Statistics). You will be passionate about science, hardworking, and excited to learn and improve your skills in an outstanding and supportive research environment. You will be part of a multidisciplinary team and will be tasked with proactively seeking and maintaining appropriate collaborations. You will also be expected to drive forward the project, working closely with biologists, clinicians and bioinformaticians within and outside the group to accomplish scientific objectives

Duties: This role will involve using engineering techniques to explore how birds sense airflow and will involve using: High-speed video and computer image analysis to measure wing motion during bird flight; Vibration engineering approaches to measure feather vibrations during wind tunnel testing of isolated wings; Dynamics analysis approaches to relate airflow to feather vibration
Requirements: You have strong experimental skills. Have a PhD in a field related to Engineering, Physics, Maths, Life Sciences or closely related discipline, or equivalent experience. You are highly motivated, willing to learn, able to take initiative and significant responsibility in a leading-edge international research project

Department: Bioinformatics Core Facility
Duties: Provide expert analysis of high-throughput genomic data, using a wide range of biological resources and bioinformatic methods; Develop methodologies and techniques to address analysis issues and implement software and data resources in relation to these technologies; Evaluate and provide software, databases, protocols and methods to aid in the analysis of genomic and genetics experiments from academic and commercial sources; Provide consultation and communication in data analysis, data mining, statistics, genomics and other areas of bioinformatics, to Crick scientists; Collaborate in developing the Core with other members of the Bioinformatics group, Crick scientists and other bioinformatics research groups within the Crick; Continue professional development through maintaining awareness of developments in the wider bioinformatics and research communities
Requirements: Higher degree in a relevant subject with an extensive analytical component e.g. bioinformatics, statistics, molecular biology or mathematics; An understanding of programming, particularly with regard to big data, data visualisation and data-mining techniques within a genomic or genetical environment; Familiarity with the application of statistical techniques to biological data; A basic knowledge of molecular biology, genetics, model organisms and possibly cancer biology; A broad comprehension of high throughput genomic technologies; A working knowledge of how to design and build data resources, and their use

Department: Department of Global Health & Development
Duties: The post holder will support Work Package 2 of the project, which will collect evidence on determinants of low vaccine uptake (barriers), and high vaccine uptake (enablers) among underserved groups in Europe. They will be involved in conducting a qualitative study to explore attitudes, intentions, and behaviours towards vaccination, specifically HPV and MMR vaccines, amongst Bangladeshi communities in London. The post holder will be involved in study recruitment, data collection, data analysis, and publication writing. They will also have the opportunity to assist in disseminating findings to community members, consortium partners, and other stakeholders
Requirements: The role will require experience in qualitative methods. Some knowledge of the UK vaccination system and experience in community engagement would be an advantage

Duties: A monotone coarse invariant (MCI) is an invariant which behaves monotonically with respect to coarse embeddings; growth and asymptotic dimension are two classical examples of such invariants. In the last ten years, the number and diversity of MCIs has increased dramatically, with new MCIs inspired by techniques from combinatorics, analysis, topology, electrical network theory and neural networks. The goal of the project is to further develop these MCIs as tools to tackle key problems in geometric group theory, fractal geometry and beyond
Requirements: You hold a PhD in Mathematics; You have expert knowledge in geometric group theory, combinatorial group theory or coarse geometry; You have demonstrated the ability to write and publish academic papers for leading international journals; You have the ability to conduct research independently and as part of a collaboration

Department: Department of Mathematics
Workload: 100%
Duties: The department has internationally recognised research groups in pure and applied analysis; fluid mechanics; mathematical physics; geometry and topology; algebra, number theory and combinatorics; mathematical modelling in biology, finance, industry and society; Applications are invited for a full-time Research Fellow position to work with Professor Erik Burman on the project Computational methods for inverse problems subject to wave equations in heterogeneous media; The responsibilities of the post will include: carrying out vigorous, high-level research in the numerical and applied analysis of inverse problems subject to the wave equation, submitting publications regularly in refereed journals; participating in local seminars and in national and international conferences. Interfacing with other team members, and full participation in seminars and colloquia in the subject
Requirements: Candidates should have a PhD or equivalent qualification in Mathematics, or Numerical Analysis on a topic related to computational methods for wave propagation, computational methods or stability analysis for inverse problems, should be finalising their PhD or waiting for their viva date. An outstanding candidate will have interest and research experience with at least some of the following subjects: theory of finite element methods, error analysis of numerical methods, knowledge of stabilised finite element methods or discontinuous Galerkin methods, stability analysis of ill-posed problems, Carleman estimates. They will also have experience of some computational finite element package (fenics, freefem etc) and their application to the numerical approximation of solutions to partial differential equations

Duties: The Operations and Supply Chain Management Group is seeking to appoint a new colleague at the level of Lecturer (the equivalent to Assistant Professor). Operations and supply chain-related research at ULMS has a broad scope and includes an increasing interest in digital business, data analytics and software engineering developments and applications to operations and supply chain design and management. Applications from those with relevant research experience, strong publication plans, and teaching interests in digital business and data analytics are of particular interest for these posts
Requirements: You will possess a relevant PhD, or be close to completion of a PhD, and will demonstrate the potential to publish in top academic journals. Candidates will be able to evidence future research plans demonstrating a capacity to sustain a high level of output, and be expected to teach subjects related to the post at undergraduate and postgraduate levels. The School seeks excellence in all aspects of student experience and looks for individuals with a passion for innovative pedagogies and the capacity to create and deliver new and highly contemporary modules

Duties: We seek to appoint an outstanding researcher to improve understanding of European winter storm risk under current and future climate conditions. This fellowship will provide an excellent opportunity to develop an academic career at the interface of mathematical and climate science that has real impact for the global insurance sector. Work will involve creating and analysing large storm data sets, developing novel physically consistent statistical methodologies for quantifying extreme storms and understanding the climate dynamics that controls how they will evolve due to low frequency natural variability and future climate change. The fellow will work closely with Prof. David Stephenson (U. of Exeter) and Prof. Adam Scaife (U. of Exeter/Met Office) and catastrophe modellers and risk analysts at Willis Towers Watson (a leading global advisory, broking and solutions company) and affiliates, as well as with other partners in the Willis Research Network
Requirements: Applicants must have a PhD in Statistics, Mathematics, Physics or a related discipline. Experience of statistical modelling of complex datasets, excellent cross-disciplinary communication and collaboration skills, and computer programming skills (e.g. in R and Python) are also essential. Knowledge of dynamical meteorology and experience of using climate model output would also be desirable. Successful candidates will have demonstrated the ability to carry out creative, innovative, independent research, and the ability to publish in peer-reviewed journals and to create practical applications of their work with industry collaborators. The successful applicant will also be able to work collaboratively, supervise the work of others and act as team leader as required

Workload: 100%
Duties: As an actuary at AIG, you will be challenged and encouraged to reach your greatest potential. Every day will bring new opportunities to stretch your analytical and problem- solving skills as you improve how we predict and mitigate risk. Our Financial Actuaries are on the frontlines, quantifying risk, pricing insurance and reserving losses for AIG’s major regulated and rated insurance operating companies globally. Portfolio Analytics and Pricing Actuaries support AIG’s businesses and are responsible for technical pricing, product development analytics and performance measurement. They collaborate with Marketing, Operations and Financial Management
Requirements: Candidates with relevant actuarial experience strongly preferred; Candidates with local language skills strongly preferred; Student member of an Actuarial Institute progressing through exams; Degree in Mathematics or related discipline; Strong analytical and problem solving skills; Work well both independently and as part of a team; Expertise in Excel, Access, VBA, SAS, or other programming languages preferred; Effective time management skills