The International Society for Bayesian Analysis

Funded PhD Positions in Bayesian Uncertainty Quantification at the University of Exeter Apr 14, 2019 The University of Exeter Mathematics department is offering up to 4 fully funded doctoral studentships for 2019/20 entry. Full details of the funding awarded, eligibility and a list of all possible projects is available here There are two advertised projects in Bayesian Uncertainty Quantification, both co-supervised by Professor Peter Challenor and Dr Daniel Williamson. One entitled "Matching covariance kernels to numerical models in Gaussian process emulation" (full description here ), the other entitled "Calibration of numerical models with deep Gaussian processes" (full description here ). Both projects will enable the successful candidate to engage with the Alan Turing Institute for Data Science and Artificial Intelligence, and to join an active group of researchers in Bayesian methods for Uncertainty Quantification for complex models, with applications in Earth system science, human health and engineering. Applications close on the 13th May 2019.

Post-Doc in Applied Bayesian Modelling at the University of Kent Jan 22, 2020 We are advertising for a postdoctoral researcher (PDRA) to work on our NERC-funded project "Integrating new statistical frameworks into eDNA survey and analysis at the landscape scale". This interdisciplinary project is led by Dr. Eleni Matechou at the University of Kent, with co-Investigators including Dr. Alex Bush (University of Lancaster), Professor Jim Griffin (Statistical Science, UCL), Professor Richard Griffiths (Durrell Institute of Conservation and Ecology, University of Kent), and Professor Doug Yu (UEA). The aim of the project is to develop an integrated statistical framework for DNA-based biodiversity surveys. We seek a PDRA with a strong research record and relevant expertise in applied Bayesian modelling and computational methods.

Judith Rousseau Laboratory: Department of Statistics, Oxford University, UK Phone: (0), Email: Webpage: rousseau/ Funding Judith Rousseau's ERC Advanced Grant 2018, "General Theory for Big Bayes" and Grenoble IDEX. Interested applicants should write to us with: a letter of interest, CV, and should require two recommendation letters. Context Bayesian deep learning brings together two of the most important machine learning paradigms: Bayesian inference and deep learning. On the one hand, Bayesian learning provides a theoretically sound framework to formalise the estimation of the architecture and the parameters of deep neural network models. On the other hand, deep learning offers new tools in Bayesian modelling, e.g. to learn flexible nonparametric priors or computationally efficient posterior distribution approximations. State of the art The field of machine learning has recently been much impacted by deep learning. Deep neural networks are now at the basis of the state-of-the-art in computer vision, natural language processing, to cite just a few. While very effective, these models are computationally costly and require large quantities of data for their many parameters to be accurately estimated. Bayesian statistics offers a theoretically well-grounded framework to reason about uncertainty, and it is one of the cornerstones of modern machine learning. At the same time, the theory at the basis of deep neural networks is not yet very well understood and its grounds must be laid out. Although the interaction between these two learning paradigms is relatively under-explored, there is a great potential of cross-fertilisation between the two. Objectives The goal of this project is to contribute new theory and practical techniques that lie at the interface of the deep learning and the Bayesian paradigms, by investigating how these paradigms can mutually benefit each other. More specifically, we have two methodological objectives: 1) leveraging successful principles of deep learning, such as hierarchies, convolutions, to build posterior distributions leading to rich data representations accounting for uncertainty quantification, and 2) making such posterior distributions practical in the large-scale regime by making use of approximations. This dichotomy yields challenges with both theoretical and algorithmic aspects, such as: building more interpretable parameter priors, scaling-up Bayesian deep learning algorithms, and gaining theoretical insight and principled uncertainty quantification for deep learning. Results The main expected theoretical breakthrough is a principled uncertainty quantification in the use of deep neural networks. This will improve our mathematical understanding of these models, but it should also help us design better algorithms. Specifically, we want to develop a new methodology that may change the way Bayesian deep neural networks are currently designed, make them more generic, simpler to use, and faster to train. Recent related publications Arbel, J. (2019). Bayesian Statistical Learning and Applications. HDR thesis, Univ. Grenoble-Alpes. Hayou, S., Doucet, A., and Rousseau, J. (2019). On the impact of the activation function on deep neural networks training. In International Conference on Machine Learning. Vladimirova, M., Verbeek, J., Mesejo, P., and Arbel, J. (2019). Understanding Priors in Bayesian Neural Networks at the Unit Level. In International Conference on Machine Learning. Wilson, A. G.(2020). The case for Bayesian deep learning.arXiv preprint arXiv:2001.10995. Environment Inria is the French national research institute for digital science and technology. World-leading research and technological innovation are an integral part of its DNA. Inria's 3,500 researchers and engineers put their passion for digital technology to work in nearly 200 project teams, most of which are joint teams with our academic partners, including major research universities and the CNRS. They explore new fields, often in collaboration with different disciplines and industrial partners, with the aim of meeting ambitious challenges. The University of Oxford is one of the world's leading academic institutions and one of the oldest, with a unique heritage that dates back to the 11th century. Today its reputation, like its longevity, reflects a deep and abiding commitment to excellence in every area of teaching and research. As a result of that commitment, the University enriches international, national and regional communities in countless ways: through the fruits of its research and the skills of its alumni, through sharing academic and cultural resources, and by publishing outstanding materials in many formats for learning and study.

Six academic positions in Statistics at the University of Warwick Department of Statistics, University of Warwick, United Kingdom Enthusiastic and excellent academics are sought to be part of the Department of Statistics at Warwick, one of the world's most prominent and most research active departments of Statistics. We are advertising six posts in total, which reflects the strong commitment of the University of Warwick to invest in Statistics. We intend to fill the following positions: • Assistant Professorship (2 posts, permanent, closing date 2 January 2019), • Harrison-early-career assistant professorship (1 post, 3 years, closing date 2 January 2019), • Associate Professorship (2 posts, permanent, closing date 31 January 2019), • Principal Teaching Fellow (1 post, permanent, closing date 28 February). You will have expertise in statistics (to be interpreted in the widest sense and to include both applied and methodological statistics, probability, probabilistic operational research and mathematical finance together with interdisciplinary topics involving one or more of these areas) and you will help shape research and teaching leadership in this fast-developing discipline. Informal enquires can be addressed to any of Professors Barbel Finkenstadt (), David Hobson (), Gareth Roberts () or to any other senior member of the Department. Applicants are encouraged to ask their referees to send letters of recommendation by the closing date to the Departmental Administrator, Mrs Paula Matthews (). More details and a link to the application form: Further information about the Department of Statistics: Further information about the University of Warwick:

Senior Teaching Associate - MRC Biostatistics Unit, University of Cambridge Jan 11, 2024 We are recruiting a Senior Teaching Associate (40 - 60% FTE) with experience of supporting, developing and delivering engaging, challenging and effective post-graduate education in population health sciences. The role will support the delivery of courses covering epidemiology, biostatistics and infectious diseases for the Masters of Philosophy in Population Health Sciences (MPhil in PHS). The successful candidate will have graduate level subject matter knowledge in a wide range of topics from epidemiology, biostatistics or infectious disease modelling and experience of programming in R / R Studio. Essential criteria for appointment include: - PhD in a relevant quantitative topic (e.g. epidemiology, biostatistics, health data science, infectious disease modelling, computer science or applied mathematics) - Ability to develop and encourage the commitment to learn in others and to present material to a range of audiences - Ability to provide pastoral assistance to students - Highly advanced knowledge of teaching of a particular subject relevant to the course involving a critical understanding of relevant theory and/or principles outside of the immediate specialism - Excellent interpersonal and communication skills - Excellent organisational skills - Ability to work collaboratively and to quickly develop strong relationships and networks with colleagues - Proven academic interest and professional experience in the field - Experience of proposing, supervising and assessing masters-level dissertation projects in relevant topics - Track record of successful development and delivery of engaging, challenging and effective teaching at masters level in relevant topics - Experience of working across a range of relevant disciplines - Previous confirmed experience of organisation, management, leadership, communication and programme development - Experience of setting and assessing authentic masters-level assessment in relevant topics - Experience of supporting students from diverse backgrounds to become self-regulated learners - Specialist knowledge in relevant topics - Knowledge of a variety of teaching delivery and assessment methods - Ability to draw from a broad range of disciplines and knowledge sources relevant to population health sciences - Commitment to equality, diversity and inclusion in teaching - Commitment to widening participation agendas in student recruitment. The funds for this post are initially available for 2 years from commencement in post. The MRC Biostatistics Unit is one of Europe's leading biostatistics research institutions. Our focus is to deliver new analytical and computational strategies based on sound statistical principles for the challenging tasks facing biomedicine and public health.

Research positions available in machine learning at all levels: Research Fellow, Postdoc, PhD student. Turing AI Fellowship, Univ Manchester, UK Still some positions available in my new research group funded by the Turing AI World-Leading Researcher Fellowship: Human-AI Research Teams: Steering AI in Experimental Design and Decision-Making. Positions are available at all stages; we seek to fill most positions now but leave some for future years as well: - Research Fellow - Postdoc - PhD Student The work involves probabilistic modelling in exciting new settings, and developing new methods for probabilistic machine learning and inference. Applicants with outstandingly strong expertise in one of following topics are welcome, or strong expertise in one and keen interest in working with expert colleagues on the others: automatic experimental design, Bayesian inference, human-in-the-loop learning, advanced user modelling, machine teaching, privacy-preserving learning, reinforcement learning, inverse reinforcement learning, simulator-based inference, likelihood-free inference. There will be particularly good opportunities to join new work on collaborative modelling and decision-making with AI. And applications in drug design, synthetic biology, personalized medicine, and digital twins. The positions are in the University of Manchester, which has recently strengthened its position as a centre for research into AI fundamentals and impactful applications, featuring: - Brand-new ELLIS Unit Manchester (press release out any minute now ) - Partnership with the Alan Turing Institute - New Centre for Fundamentals of AI, with a number of excellent new faculty members joining - Institute for Data Science and AI, with >900 researchers - Excellent university with outstanding collaborators in other strong fields within a walking distance on the same campus - Dual positions can be negotiated with research groups in cancer research, biotechnology, digital twins, medicine and health, both in academia, hospitals and companies. Get in touch. - Most livable city in the UK More info on the Turing AI World-Leading Researcher Fellowships:

Postdoc in Bayesian machine learning, AstraZeneca, Cambridge, UK Mar 29, 2018 PREDICTING DRUG TOXICITY WITH BAYESIAN MACHINE LEARNING MODELS We're currently looking for talented scientists to join our innovative academic-style Postdoc. From our centre in Cambridge, UK you'll be in a global pharmaceutical environment, contributing to live projects right from the start. You'll take part in a comprehensive training programme, including a focus on drug discovery and development, given access to our existing Postdoctoral research, and encouraged to pursue your own independent research. It's a newly expanding programme spanning a range of therapeutic areas across a wide range of disciplines. What's more, you'll have the support of a leading academic advisor, who'll provide you with the guidance and knowledge you need to develop your career. You will be part of the Quantitative Biology group and develop comprehensive Bayesian machine learning models for predicting drug toxicity in liver, heart, and other organs. This includes predicting the mechanism as well as the probability of toxicity by incorporating scientific knowledge into the prediction problem, such as known causal relationships and known toxicity mechanisms. Bayesian models will be used to account for uncertainty in the inputs and propagate this uncertainty into the predictions. In addition, you will promote the use of Bayesian methods across safety pharmacology and biology more generally. You are also expected to present your findings at key conferences and in leading publications This project is in collaboration with Prof. Andrew Gelman at Columbia University, and Dr Stanley Lazic at AstraZeneca. Education and Experience Required: - PhD in Statistics, Computer Science, Data Science, or similar - Excellent knowledge of either R or Python (ideally both) - Knowledge of Bayesian statistics - Knowledge of modern Bayesian software such as Stan and PyMC3 - Knowledge of (or an interest in) life sciences This is a 3 year programme. 2 years will be a Fixed Term Contract, with a 1 year extension which will be merit based. The role will be based at Cambridge, UK with a competitive salary on offer. To apply for this position, please follow the link below:

Postdoc at Oxford: Machine Learning & Global Health Date: Jan 11, 2023 We are hiring a postdoctoral researcher to join my group in the Department of Computer Science at Oxford, working with the Machine Learning & Global Health network on machine learning applications for public policy and global health. This position is funded by EPSRC. For more details, see this link . The role involves leading research in computational statistics and machine learning, with the goal of making a tangible impact by collaborating with governments, NGOs, and international organizations. Recent publications from the group include: List of publications or specify if unavailable If you have any questions, please contact me directly or reach out to members of the Machine Learning & Global Health Network .

Four academic positions in Statistics at the University of Warwick, UK (all levels) Enthusiastic and excellent academics are sought to be part of the Department of Statistics at Warwick, one of the world's most prominent and most research active departments of Statistics. We are advertising four posts in total, which reflects the strong commitment of the University of Warwick to invest in Statistics. We intend to fill the following positions: • Assistant or Associate Professor of Statistics (two positions) • Reader of Statistics • Full Professor of Statistics. All posts are permanent, with posts at the Assistant level subject to probation. You will have expertise in statistics (to be interpreted in the widest sense and to include both applied and methodological statistics, probability, probabilistic operational research and mathematical finance together with interdisciplinary topics involving one or more of these areas) and you will help shape research and teaching leadership in this fast-developing discipline. Applicants for senior positions should have an excellent publication record and ability to secure research funding. Applicants for more junior positions should show exceptional promise to become leading academics. While the posts are open to applicants with expertise in any field of statistics (widely interpreted as above), the Department is particularly interested in strengthening its existing group in Data Science. The Department is heavily involved in the Warwick Data Science Institute and the Alan Turing Institute, the national institute for data science, headquartered in London. If interested, a successful candidate can apply to spend part of their time at the Alan Turing Institute as a Turing Fellow. Informal enquires can be addressed to addressed to Professors Mark Steel (), Gareth Roberts () and David Firth () or to any other senior member of the Warwick Statistics Department. Closing date: 3 January 2018 for the Assistant/Associate level posts and 10 January 2018 for the Full Professor position. Applicants at Assistant/Associate levels should ask their referees to send letters of recommendation by the closing date to the Departmental Administrator, Mrs Paula Matthews (). More details and a link to the application forms: Further information about the University of Warwick: Further information about the Department of Statistics:

University of Warwick, UK: Three permanent positions in Statistics Outstanding and enthusiastic academics are sought to be part of the Department of Statistics at Warwick, one of the world's most prominent and most research active departments of Statistics. The department has close relations with the co-located Mathematics Institute and Department of Computer Science and with other departments such as Economics and the Warwick Business School, and is strongly engaged with the Alan Turing Institute in London. We are advertising three permanent posts, which reflects the strong commitment of the University of Warwick to invest in Statistics. We are looking for applicants with evidence or promise of world-class research excellence to join the Department at Assistant or Associate Professor level. You will have expertise in statistics (to be interpreted in the widest sense and to include both applied and methodological statistics, machine learning and financial data modelling, together with interdisciplinary topics involving one or more of these areas). You will help shape research at Warwick in this fast-developing discipline and deliver high quality teaching across our broad range of degree programmes. Applicants at the Associate Professor level should have an excellent publication record. Other positive indicators include a proven ability to secure research funding and a track record of research impact outside of the area of academic dissemination. Applicants at the Assistant Professor level should show exceptional promise to become internationally leading academics. The Department of Statistics is committed to promoting equality and diversity, and holds an Athena SWAN Bronze award demonstrating this commitment. We welcome applicants from all sections of the community and will give due consideration to applicants seeking flexible working patterns and to those who have taken a career break.

Assistant Professor position in Statistics at Warwick The Department of Statistics at Warwick University spans a broad range of areas in applied, computational, methodological and theoretical statistics, data science, theoretical and applied probability, mathematical finance and interdisciplinary collaboration. Its teaching programmes attract exceptional students at all levels. We are looking to appoint an Assistant Professor with a strong research track record and outstanding promise in one or more areas of Computational, Methodological or Theoretical Statistics, or Machine Learning. The successful candidate will be expected to deliver excellent teaching and student project supervision in Statistics, Data Science and related areas. Other positive indicators include enthusiasm for engagement with other disciplines, within and outside the Department. Further details of the requirements for the position can be found at The Department of Statistics is committed to promoting equality and diversity, holding an Athena SWAN Silver award which demonstrates this commitment. We welcome applicants from all sections of the community and will give due consideration to applicants seeking flexible working patterns, and to those who have taken a career break. Further information about working at the University of Warwick, including information about childcare provision, career development and relocation is at Informal enquires can be addressed to Professor Jon Forster (), Professor Ioannis Kosmidis (), Professor Gareth Roberts () or to any other senior member of the Warwick Statistics Department.

Research Associate in Modern Statistics, Global Health, and Conservation Ecology Jul 24, 2023 Salary Range: £43,093- £50,834 per annum Fixed Term for initially 12 Months with extension likely Start date: 1 October 2023 or soon thereafter This is an exciting opportunity to help lead an ongoing programme of methodological research to tackle pressing global health problems in collaboration with leading international organisations. The focus of this post is on the development of novel, flexible and computationally tractable spatio-temporal statistical inference tools in Bayesian Statistics and AI, and on their application in three domains. Applications range from HIV deep-sequence phylogenetics within the PANGEA-HIV consortium, to quantification and hotspot mapping of caregiver loss with the Global Reference Group for Children Affected by COVID-19 and in Crises, and species mapping and forecasting using oceanographic and climatological datasets. You will have access to some of the finest longitudinal datasets in Africa and South America. Post holders will interact with a team of leading researchers. They will receive hands-on training in machine learning and modern statistics, epidemiological, and phylogenetic techniques, and will be mentored by leading scientists, who often publish in some of the top journals of the field. Your base will be in the Department of Mathematics at Imperial College London, and you will work closely with the Machine Learning & Global Health Network (MLGH), a multi-institution research laboratory with members at Oxford, Imperial College London, University of Copenhagen, and Singapore. Post holders will be reporting directly to Dr Oliver Ratmann (Imperial), and collaborating closely with Professor Seth Flaxman (Oxford), Dr Kate Grabowski (Johns Hopkins), Dr Ettie Unwin (Bristol), Dr Adam Sykulski (Imperial), and Professor Christophe Fraser (Oxford).

IMSS Senior Research Fellow in Statistical Science Aug 20, 2021 We are recruiting for two IMSS Senior Research Fellows in Statistical Science to join UCL on a full time basis (job shares considered) on Grade 8 £44,737- £52,764 per annum inclusive of London Allowance. You will lead and carry out a programme of original independent research on a topic of your choice in statistics (including data science) or applied probability, leading to conference presentations and publications in leading journals. You will also contribute to the research environment of the departments of Statistical Science and of Mathematics. A strictly limited amount of teaching will also be required. Appointees will each be awarded a fund of £9,000 to support their research over the duration of the fellowship. Two fellowships are available from October 2021, each of three years' duration in the first instance. Fellows are expected to be in post by 31st March 2022. A PhD or equivalent qualification, or evidence of an equivalent level of attainment in research publications, in statistics or a closely related field; a proven record of ability to carry out high quality research in a branch of probability or statistics, including publications in highly regarded peer-reviewed journals; and ability to plan and implement an influential independent research programme. Closing on 27 September 2021. Visit UCL Department of Statistical Science for more information.

Research Associate in Bayesian Non-Parametric statistics at Imperial College London Apr 24, 2018 Applications are invited for a Research Associate position in the Department of Mathematics at Imperial College London to work in the area of Bayesian Non-Parametric statistics. The position is funded through the EPSRC Grant EP/R013519/1. The Research Associate will work directly with Dr Sarah Filippi who holds a joint position between the Department of Mathematics and the School of Public Health. The advertised position is based in the vibrant Statistics section of the Department of Mathematics, and is to work in collaboration with researchers in the School of Public Health and at the MRC-PHE Centre for Environment and Health. The post holder will work on developing a novel Bayesian Non-Parametric Test for Conditional Independence. This is at the core of modern causal discovery, itself of paramount importance throughout the sciences and in Machine Learning. As part of this project, the post holder will derive a Bayesian non-parametric testing procedure for conditional independence, scalable to high-dimensional conditioning variable. To ensure maximum impact and allow experimenters in different fields to easily apply this new methodology, the post holder will then create an open-source software package available on the R statistical programming platform. Doing so, the post holder will investigate applying this approach to real-world data from our established partners who have a track record of informing national and international bodies such as Public Health England and the World Health Organisation. This should position the post holder ideally for the next steps in their career, by furthering their track record of bridging theory and applications in concrete ways. The successful candidate must hold a PhD, or equivalent level of professional qualifications in statistics, mathematics, computer science or closely related discipline. It is essential that you have: Experience and knowledge: Desire to develop statistical methodology for conditional independence testing in a Bayesian Non-Parametric framework. Experience in carrying out research of high quality, independently and/or in a team, evidenced by publications of high quality. A strong background in statistics . Skills and abilities: Ability to work and communicate effectively in a multi-disciplinary team Ability to carry out original research and publish in high impact journals Ability to exercise initiative and judgment in carrying out research tasks Ability to prioritise own work in response to deadlines Ability to identify, develop and apply new concepts, techniques and methods Creative approach to problem-solving Ability to organise and prioritise own work with minimal supervision Ability to keep accurate records of research results and activity Excellent written communication skills and the ability to write scientifically, clearly and succinctly for publication Ability to present research with authority and coherence Please complete and upload an application form as directed, also providing a CV and a list of publications. For any specific queries regarding the post please contact Dr Sarah Filippi () Should you have any queries about the application process please contact Ms Mona El-Khatib, (). For technical issues when applying online please email

Chair (full professor) and Assistant Professor in Statistics, Durham University, United Kingdom Oct 3, 2017 The positions are in the Department of Mathematical Sciences at Durham University, United Kingdom. Full details for the Chair are available from and for the Assistant Professorship from Informal enquiries are welcome: to Professor Peter Craig () for the Chair and to Dr Ian Jermyn () for the Assistant Professorship. Applications must be made via the Durham University's vacancies portal: for the Chair and for the Assistant Professor position. The closing dates are November 6th 2017 for the Chair and November 22nd 2017 for the Assistant Professorship; applications must be submitted by 12:00 GMT on the closing date. Further information about relocation, benefits and so on is available from menus on the portal. The statistics and probability group currently has 17 permanent academic staff (11 in statistics), 3 post-docs and 27 research students. Uncertainty quantification is a common theme of our research interests which include Bayesian, Bayes linear and non-parametric statistics, and statistical modelling of structure and shape. There is a strong emphasis on foundations, including imprecise probability. Interdisciplinary collaborations within and outside the university on a wide range of applications, in particular those involving computer models, are supported by funding from research councils and industry. Solutions provided to companies and government organisations led to 6 highly rated impact case studies for the UK Research Excellence Framework evaluation in 2014. The new positions are part of significant growth in the group and department, funded largely by an increase in undergraduate numbers. Durham University and the Department rank very high in the UK for undergraduate education and attract excellent students. An enhanced undergraduate offering, including new degree programmes in statistics, is part of the plan for growth and, by 2020, the department will have a new building, shared with Computer Science. Both appointees will contribute to, and help shape the future of, the research and teaching of the Department and will be good citizens contributing to department administration and other wider university activities. The Chair will also share leadership in statistics with senior colleagues. The Department embraces excellence in all its forms and invites all qualified candidates to apply. Durham University is an Equal Opportunities employer; see

Lecturer or Senior Lecturer (Assistant Professor) in Statistics (Imperial College London) Apr 25, 2022 Applications are invited from outstanding individuals for a Lecturer or Senior Lecturer in Statistics, to start from October 2022, or a date to be agreed. The position is permanent, full time, with internationally competitive salary, plus benefits. For this opening, we are interested in hiring an excellent candidate in ANY area of Statistics or Applied Probability. With 30 academic staff, many postdoctoral researchers, and over 50 PhD students the Section offers an engaging, diverse, and lively research culture in Statistics. The Section is based in the Huxley Building on an attractive site in South Kensington in the internationally-significant Albertopolis cultural district in central London. The members of the section are involved in a range of activities including lectures, workshops, seminars, departmental colloquia and a rich range of collaborations with academic, industry and government. The Statistics Section is also a key player in IX: an exciting new strategic initiative providing an environment for research, education and entrepreneurship across artificial intelligence, data science and digital technologies based at Imperial's White City campus. Further details of the Section and its activities are available on Statistics Section's website .

Lecturer / Senior Lecturer in Statistics, Imperial College London Lecturer / Senior Lecturer in Statistics, Imperial College London Full-time, permanent The Statistics Section of Imperial's Department of Mathematics is undergoing significant expansion and seeks applications for multiple new Lectureships starting 1 January 2021, or as soon as possible thereafter. This expansion includes developing and deploying a new MSc programme that will be delivered entirely online. In terms of focus, the Section is committed to serious interdisciplinary research, the development of methods for solving applied problems and the statistical theory underlying these methods. Applicants with strong track records of excellence in research and teaching are encouraged to apply. Applicants with teaching and research expertise in Statistical Finance, broadly interpreted, are particularly welcome. Further information about the Statistics Section can be found at . There are two positions available, starting 1 January 2021, or as soon as possible thereafter. The positions are available full-time but part-time may be considered for exceptional candidates. Further information about the Department, and further particulars of the post, can be found at the website

full-time/permanent Lecturer/Senior Lecturer (equiv Assistant/Associate Professor) in Statistics at Imperial College London Jan 30, 2024 Imperial College London invites applications for a full-time permanent faculty position at the Lecturer (equivalent to Assistant Professor) level, based in the Statistics Section of the Mathematics Department. Imperial College London is a world-leading university renowned for excellence in research and teaching, attracting top-tier students and staff globally. Our faculties include Engineering, Natural Sciences, and Medicine, along with the Imperial College Business School, fostering interdisciplinary collaboration across science, medicine, engineering, and management. The position offers an attractive salary package, including a pension scheme with significant employer contributions, and generous terms of employment. It is a permanent role, akin to a tenured position. Benefits include subsidised childcare, flexible working policies, professional development opportunities, sabbaticals, and free NHS healthcare. We also support dual-career couples with advice and assistance. The Statistics Section serves as a hub for data science research at Imperial, supporting data-driven research across various fields such as astrophysics, biology, medicine, finance, and social sciences. It offers a vibrant research environment, linking to initiatives like the Data Science Institute, Mathematics in Medicine, Machine Learning, and Artificial Intelligence networks. The section comprises 34 staff members, 60 PhD students, and 8 postdoctoral researchers, fostering growth and collaboration in statistics and data science.

Bayesian methodology postdoc - University of Cambridge, MRC Biostatistics Unit, UK Oct 12, 2023 This is an exciting opportunity for an ambitious post-doctoral research associate to join the MRC Biostatistics Unit to carry out methodological research relating to Bayesian inference. The post-holder will focus on developing novel Bayesian statistical methodology to improve the analysis and understanding of biomedical data, particularly relating to population health and/or patients in hospitals. Depending on their skills and interests, there are several potential directions that the postholder could pursue. See for further details. The MRC Biostatistics Unit undertakes research on statistical methods and their application to the design, analysis and interpretation of biomedical studies, to advance understanding of the cause, natural history and treatment of disease, and to evaluate public health strategies. It is one of Europe's leading biostatistics research institutions and includes many internationally renowned statisticians. The Unit is situated on the Cambridge Biomedical Campus, one of the world's most vibrant centres of biomedical research, which includes the University of Cambridge's Clinical School, two major hospitals, the MRC Laboratory of Molecular Biology, and the world headquarters of Astra Zeneca. The Unit provides a privileged environment for conducting research within the Cambridge biomedical environment. The Unit is actively seeking to increase diversity among its staff, including promoting an equitable representation of men and women. The Unit therefore especially encourages applications from women, from minority ethnic groups and from those with non-standard career paths. Appointment will be made on merit. The University actively supports equality, diversity and inclusion and encourages applications from all sections of society. We welcome applications from those wishing to work part-time. The University has a responsibility to ensure that all employees are eligible to live and work in the UK. Fixed-term: The funds for this post are available for 3 years in the first instance.

Assistant and Associate Professor positions in Statistics and Machine Learning at Warwick Outstanding and enthusiastic academics are sought by the Department of Statistics at Warwick, one of the world's most prominent and most research active departments of Statistics. The Department has close relations with the co-located Mathematics Institute and Department of Computer Science and with other departments such as Economics and the Warwick Business School. Four permanent posts are available, which reflects the strong commitment of the University of Warwick to invest in Statistics and Machine Learning: Associate Professor, Statistics Applicants should have evidence or promise of world-class research excellence and ability to deliver high quality teaching across our broad range of degree programmes. At Associate Professor level, applicants should have an outstanding publication record. Other positive indicators include enthusiasm for engagement with other disciplines, within and outside the Department and, at Associate Professor level, a proven ability to secure research funding. Further details of the requirements for each of the four positions can be found at The Department of Statistics is committed to promoting equality and diversity, holding an Athena SWAN Silver award which demonstrates this commitment. We welcome applicants from all sections of the community and will give due consideration to applicants seeking flexible working patterns, and to those who have taken a career break. Further information about working at the University of Warwick, including information about childcare provision, career development and relocation is at Informal enquires can be addressed to Professors Jon Forster () or Adam Johansen () or to any other senior member of the Warwick Statistics Department.