Duties: Lead Model Validation activities for the IMM model suite, including prioritization of the Book of Work for the team; Conduct independent testing to assess model accuracy and robustness under different scenarios and market conditions, including, where appropriate the evaluation of developer documentation and testing; Assess, quantify and communicate to stakeholders model risks due to model limitations and compensating controls; Develop and apply high-quality validation standards by conducting independent testing to assess model accuracy and robustness under different market conditions; Highlight risks and limitations of models and communicate findings to stakeholders, senior management, and governance committees
Requirements: Masters or Ph.D. degree (or equivalent) in Finance, Mathematics, Physics, or a related quantitative field; The ideal candidate has strong experience with counterparty credit risk modelling framework gained at a financial institution, including experience facing regulatory requests; The ability to effectively communicate with a wide range of stakeholders (incl. senior management and internal/external auditors), both written and verbally

Duties: Development, enhancement and maintenance of market risk capital forecasting models under stress scenarios to ensure ongoing appropriateness and adaptations to new regulations (e.g. FRTB); Contribution to key regulatory deliverables and programs (e.g. FRTB) as well as analysis and interpretation of key regulatory requirements; Perform ongoing monitoring and evaluation of market risk capital forecasting models, review existing models to ensure they remain fit for purpose and make improvements where necessary; Collaborate closely with the model validation team to understand validation findings and remediate any identified issues
Requirements: MSc or equivalent in a quantitative subject (such as quantitative finance, statistics/mathematics, sciences or engineering); Deep understanding of quantitative risk including good knowledge of financial products and their risk representation; Demonstrable experience in delivering enhancements to risk models; Excellent mathematical, analytical, problem solving and troubleshooting skills

Duties: You will be responsible for conducting processing and detailed analysis of a variety of ‘omics datasets, including bulk and single cell transcriptomic data, whole-genome and exome DNA sequencing data, proteomic data and metabolomic data across a range of parallel projects. You will provide bioinformatics advice to the IMCM research project teams and plan new analyses that will progress the IMCM research projects. Keeping meticulous, detailed records of your work and committing to performing cloud-based analyses on the IMCM data platform is a key part of this role, along with preparing manuscripts for publication and contributing to written and oral presentations/reports as required
Requirements: It is essential that you hold a relevant post-graduate qualification in bioinformatics, computational biology, biostatistics, applied mathematics, or related discipline, and have experience handling and analysing various types of ‘omics data types, such as RNA-Seq, whole genome or exome sequencing data, single cell profiling, ChIP-Seq, proteomics, and metabolomics. You will be able to plan and oversee programmes of technical work to a successful conclusion by agreed deadlines. Experience of programming languages including Python and R is essential, along with experience of developing and maintaining bioinformatics pipelines and workflows. Previous experience of working on neuroscience projects, such as on Parkinson’s disease, Alzheimer’s disease, ALS or another neurodegenerative disease is highly desirable

Duties: This exciting role will undertake research on first-principle electromagnetic channel modelling that includes but is not limited to: Advanced electromagnetics methods for universal channel modelling, numerical methods for wave propagation in complex environments, statistical electromagnetics, computational electromagnetics, implementation of full-wave commercial solvers (e.g., COMSOL), standard 3GPP channel models
Requirements: A PhD degree (or equivalent) in Electronic Engineering, Applied Mathematics, Physics or other areas related to RF/Microwave Engineering; Expertise in advanced theoretical and computational electromagnetics; Recent research experience in the development of first-principle wave models; Recent research experience in the development of numerical codes for complex electromagnetic scattering scenarios, and the use of full-wave commercial electromagnetics software; Good knowledge of the main standard channel models (e.g., 3GPP)

Duties: With the continued growth of our market access, health economics and healthcare value demonstration teams we are looking to add to our team with the addition of a talented Senior Health Economist. You will have a genuine passion for understanding and communicating the value of healthcare through economic modelling and data analysis. This position will act as a Technical Lead for assigned health economics and other projects; mentor junior health economists; contribute to the growth and development of PROVE’s health economic solutions
Requirements: Post graduate qualification in Health Economics, epidemiology, statistics or medical sciences; In-depth understanding of the perspectives and evidence needs of a variety of stakeholders; Ability to demonstrate strategic insights; Experience in reviewing project deliverables

Duties: We are looking to expand the Statistical and Programming Team with a statistical SAS Programmer including Senior and Principal roles depending on experience. The clinical data we analyse is diverse and sometimes complex compared to much clinical trials data. You will have a logical mind to unravel the detail in the data and enjoy the challenge of what at times requires intricate data manipulation. Programmers work closely with their statistics and psychometric colleagues in a small, tightly knitted team
Requirements: You will have a graduate degree in Mathematics, Computer Science, Biostatistics/Statistics, Educational Measurement or equivalent experience in statistical SAS programming

Duties: Design, implement, and operate robust, scalable genomic data processing pipelines using Nextflow on AWS; Manage pipeline results using big data technologies (e.g. distributed databases); Manage pipeline-related assets to ensure that they are findable, accessible, interoperable and reusable; Apply best practices for version control, testing, and documentation; Ensure data quality and integrity by implementing and maintaining rigorous quality control and data validation procedures; Collaborate closely with platform scientists, data scientists, and data engineers to solve complex data processing and analysis challenges
Requirements: MSc or PhD or equivalent in bioinformatics, computational biology, computer science, or similar discipline; 3-plus years of post-graduate or industry experience developing high-throughput bioinformatic data processing pipelines; Experience in NGS mapping, variant calling and variant analysis preferred; Experience in bioinformatics workflow frameworks (NextFlow), version control systems (Git), Cloud (AWS preferred), and containers (Docker preferred); High level of proficiency in Python or equivalent and Linux

Duties: Providing input on study design within protocols; Writing statistical analysis plans and preparing associated table shells, with the support of more experienced members of the team; Leading the execution of psychometric analyses and interpreting results, with awareness of regulatory requirements; Drafting and reviewing study reports, publications, and other deliverables; Presenting the results of psychometric analyses externally and liaising with clients on psychometric queries; Serving as a psychometric consultant internally for Adelphi Values; Providing internal training on relevant psychometric methodology
Requirements: Masters in statistics, psychometrics, psychology, educational measurement, or a related field; or equivalent experience; Knowledge of relevant psychometric methods; Knowledge of latent variable models including factor analysis and item response theory

Duties: Achieve results through detailed goal setting, accountability measures, effective partnership, performance management, collaboration with other groups and a dedication to serving customers, both inside and outside of CfDA (Center for Design & Analysis); Influence and supply to strategy development, defend statistical approaches and represent GBS (Global Biostatical Science) through participating in and collaborating with multidisciplinary study teams; Provide statistical contributions, statistical review, and quality control of Key Design Elements (KDE) protocols, randomisation specifications, Statistical Analysis Plans (SAPs), Table, Listing and Figure (TLF) shells, Submission Data File (SDF) specifications, other key study related documentation, protocol deviations, Flash Memos, Clinical Study Reports (CSRs), clinical publications, and other communications
Requirements: Degree educated in Statistics/Biostatistics or related subject with high statistical content; Post-graduate statistical experience in the pharmaceutical industry or medical research; Knowledge of SAS, R or other statistical software; Excellent communication skills and ability to work optimally within teams while also possessing the capacity to autonomously manage tasks and projects

Duties: As a Machine Learning Engineer, you will work closely with science teams to bring research to production. This is a role that combines engineering knowledge, technical strength, and product focus. It will be your job to implement novel ML systems, product integrations, and performance optimizations. You will guide the direction of a MLOPS automation framework via collaboration with the engineering and research communities
Requirements: 3+ years of non-internship professional software development experience; 3+ years experience and knowledge in MLOps, in deploying, operationalizing, and maintaining scalable AI/ML-solutions in production

Duties: Our researchers have a challenge: disproving the efficient market hypothesis every day. This requires them to harness massive compute power and to use state-of-the-art ML techniques; published in recent conferences or developed entirely in-house; as textbook methods won’t beat the competition. ML is integral to develop successful investment management strategies; it is one of the core drivers of our overall performance and success. It has long been a key tool at G-Research and we count a range of ICML and NeurIPS published researchers among our people
Requirements: Either a post-graduate degree in machine learning or a related discipline, or commercial experience developing novel machine learning algorithms. We will also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle; Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inference; Excellent reasoning skills and mathematical ability are crucial: off-the-shelf methods don’t always work on our data so you will need to understand how to develop your own models

Duties: In this role you will be responsible in leading the strategic, statistical thinking and contributions to the Development Plans, Regulatory Strategy, Health Technology Assessment and Commercial Presentation for indications/projects within an AZ product team. You will provide leadership to statistical staff on the indications/projects so that all work is carried out with regards to AZ standards and external regulations; through partnership with experts, developing design options and providing high quality decision support to enable the business to make informed decisions; quantifying the benefit, risk, value and uncertainty of the emerging product profile
Requirements: MSc or PhD degree in Statistics, Biostatistics, or related quantitative fields, or equivalent course work/technical experience; Understanding of regulations/developments in the area of Clinical Development and Biostatistics; Appropriate experience as a statistician for the relevant position level with clinical trials, pharmaceutical development, regulated research, and/or related areas of statistical applications

Duties: We are looking for a Research Fellow to join our team working on stochastic analysis, with a focus on regularisation by noise phenomena
Requirements: 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

Duties: We are seeking an outstanding candidate for a lectureship in Statistical Learning, interpreted broadly, as part of an expansion in Artificial Intelligence and Data Science research and education in the School of Mathematical Sciences. This position arises thanks to a significant new investment by the University to support our ambitions to further develop our strengths in this important area
Requirements: A PhD or equivalent professional qualifications and experience in a relevant discipline; Ability to obtain peer-reviewed funding; Evidence of distinction in research through high-quality publications; Ability for undergraduate and postgraduate teaching

Duties: We are seeking an outstanding candidate for a Lectureship in broadly interpreted Optimisation for Machine Learning and AI within the School of Mathematical Sciences at the University of Southampton
Requirements: a doctorate and postdoctoral experience in a relevant discipline; ability to obtain peer-reviewed funding; evidence of distinction in research through high-quality publications; ability for undergraduate and postgraduate teaching

Duties: Our Mission Award proposal aims to utilise Engineering Biology approaches for the development of transferable strategies to engineer antibiotic-producing Streptomyces bacteria able to use a wide range of sustainable feedstocks for production of drug molecules. To deliver this mission we will integrate ‘wet ’and ‘dry ’laboratory data from an authentic industrial Streptomyces strain lineage. We will determine how the strain improvement process has driven strains to adapt to specific media and fermentation conditions and then use this information to build, design and test appropriate engineering strategies for the development and construction of Streptomyces strains that use greener carbon sources. This will ultimately enable us to learn how to rationally design of strains for greener manufacturing and make this strategy broadly applicable to other industrial Streptomyces
Requirements: We are looking for a Research Fellow with expertise in metabolic modelling and computational biology and their application for the analysis of metabolism and the design of strategies for improving the properties of microbial strains. The appointed researcher will design and construct metabolic models based on the information collected from multi-omics experiments carried out by the collaborators, and suggest and propose experiments to select the best producing species and test their performance under diverse culture conditions

Duties: The university offers support of academics from a broad range of career paths, whether you are an established academic who currently holds an equivalent position, or a successful academic seeking an opportunity to grow into a more senior role, this is the place to do something truly unique with your expertise. You will have experience in bioinformatics, epidemiology, systems biology, large-scale ‘Omics data analysis, human centric artificial intelligence, machine learning or large data management. We are seeking candidates whose expertise spans these backgrounds with a track record and demonstrated curiosity for interdisciplinary research
Requirements: To apply, you will need a PhD, or equivalent professional qualifications, with a strong publication record, and able to demonstrate delivery of teaching in a manner that meaningfully engages students. You will have a track record of innovative research in one or more of the following: Computer Science, Health Data Science, Health Research Method Development and Analysis, Bioinformatics, Epidemiology, Public Health, large-scale ‘Omics data analysis, or systems biology; and have a desire to build a strong interdisciplinary research team with the support Medicine and ECS

Duties: You will produce high quality research outputs and contribute to writing competitive grant funding applications in relation to vasculitis and genetic epidemiology. You will also have an opportunity to supervise postgraduate research students undertaking work in this area
Requirements: Applicants will have an MSc or other higher degree in epidemiology, statistics or a related analytical subject or equivalent experience of working in an applied health research or basic science environment. Knowledge and working experience of advanced statistical techniques in medical research are essential while experience of the analysis of germline genetic data would be beneficial

Duties: The purpose of this role is to drive performance across our functions in line with our plans for profitable growth. You’ll play a pivotal role in setting our pricing strategy, setting plan targets and working with the business to deliver to these targets. This is a high priority role, you will collaborate and build relationships throughout Finance, Underwriting and the wider business, preparing and communicating key information to senior stakeholders. You’ll manage Unum’s active product portfolio, recommending dynamic pricing actions to optimise profitable growth across our products. You will be commercially minded, ensuring our pricing approach is aligned to our wider strategic goals, while also developing our pricing MI to better utilise available data and deliver meaningful insights
Requirements: Qualified actuary (preferred); Experience in commercial pricing within the insurance industry; Detailed knowledge of the life and/or general insurance industry; Strong communication and interpersonal skills, with the ability to lead relationships with other teams and produce clear and concise reports; The ability to work under pressure, deliver expected results and managing competing and conflicting demands within the workload

Duties: Responsible for projects managed by our FSP partners per Amgen Global Statistical Programming (GSP) Quality Oversight Plan (QOP); Ensure that FSP programming meets quality, compliance, timeline, and productivity expectations; Align FSP assignments with Amgen Development priorities; Responsible for FSP performance metrics development, data collection, and reporting and lead the GSP continuous improvement initiatives
Requirements: Bachelors degree or equivalent in Computer Science, Statistics, Mathematics, Life Sciences or other relevant scientific subject; Extensive SAS programming and reporting experience including SAS Base, Macro, STAT, Graph, and SQL, among others; Detailed understanding of clinical trial processes in the biopharmaceutical industry, from data collection to analysis reporting; Ability to lead programmers in successful completion of all study programming activities and provide mentorship on technical and process related questions

Duties: Pricing of individual risks in collaboration with underwriters; Preparing and communicating results to underwriters; Continual improvement of existing processes to enhance efficiency, accuracy, and transparency; Assisting in developing and maintaining risk databases for internal monitoring; Liaising with other areas of the business as required; Developing good working relationships with the underwriters
Requirements: A PhD or stand-alone Master’s in a numerate discipline would be advantageous; Excellent academic background of a technical/mathematical nature; Educated to degree level with a 2: 1 or higher; Either excellent Excel skills or experience with programming languages such as VBA, R, Python, or C++

Duties: The successful applicant will contribute to our existing portfolio of research projects, applying an economic perspective to the quantitative analysis and evaluation of health, social and mental health policy at the intersection of demand for and supply of health and social care
Requirements: Master’s level qualification in health economics/economics or another quantitative subject; Knowledge in applied economics and econometrics to engage in high quality research; Knowledge of health economics, or a strong interest in learning about the application of economics to health issues

Duties: Leading team of data scientists and ML researchers; Interfacing with HW architecture teams; Interfacing with SW framework teams; Driving model/HW codesign; Developing and analyzing novel NN architectures; Inventing novel data formats
Requirements: Proficient years of experience in ML research; Track record of leading high performance teams and delivering novel results in the field of ML; Hands on experience training and inference neural networks in frameworks such as Pytorch; Strong connections to leading academic labs; Outstanding communication skills

Duties: The principal responsibility will be to work with scientists to improve the efficiency of laboratory based research and preclinical studies, and drive the use and implementation of innovative statistical methods in the design, analysis and reporting of the research; To determine appropriate statistical methods for use in research, and draft statistical analysis plans under the mentorship of more senior statistical colleagues. Examples of methods that might be required include machine learning applied to molecular data, pathology imaging and routinely collected data; To undertake statistical analyses and prepare reports for project teams; To liaise with project teams to provide statistical input to the preparation of papers for publication, or for presentation at conferences; To contribute to the teaching of biomedical statistics within the Institute/Faculty, prepare suitable instructional material and websites and assist in the supervision of students if required
Requirements: PhD in biostatistics or bioinformatics with a substantial component relevant to the design of experiments in preclinical research. (Applicants without a PhD would be encouraged to undertake and a complete a PhD within the timelines specified by the university’s PhD regulations); Technical and methodological statistical skills relevant to laboratory based or preclinical medical research; Experience of using or aptitude to learn machine learning methods for multidimensional data analysis; Evidence of completed research and published research projects, or equivalent; Knowledge of one or more statistical analysis packages (SAS, STATA, R)

Duties: The successful candidate will work with leading researchers in stochastic analysis and data science at Oxford as part of a larger, multidisciplinary team. They will manage and conduct their own academic research and administrative activities, write up their results for publication and participate fully in the activities of the research community at Oxford. Potential research directions include, but are not limited to, scalable optimization algorithm development and analysis; stochastic processes and rough paths; reduced precision and parallel-in-time computations; high-dimensional matrices and tensors and their decompositions; hypergraphs models; learning of non-Euclidean data; and sparse deep neural networks
Requirements: Applicants will have, or be close to completing, a PhD in mathematics or a related discipline, and possess sufficient specialist knowledge and research experience in one or more of the areas of data science, machine learning, numerical analysis, optimization, scientific computing and their applications, to work within established research programmes. They will have excellent communication skills, including the ability to write for publication, present research proposals and results, and represent the research group at meetings