The official conference app for 2021 World Meeting of the International Society for Bayesian Analysis

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Jobs Posted on the Whova Community Board of 2021 World Meeting of the International Society for Bayesian Analysis

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Assistant, associate or full professor of Statistics
ITAM
Full time job, 40 hours a week. Duties are teaching undergraduate and graduate courses and doing research. The department of statistics at ITAM currently has 10 members with interest on Bayesian statistics, econometrics, machine learning and statistical computing.
Requirements are: PhD in Statistics or related field and having proved capacity for doing research and show capacity for teaching.
Link: None
Post-doc to work on developing Bayesian workflow at Aalto university
Aalto University
Postdoc position to work on developing theory, methods and tools for Bayesian workflow in highly collaborative environment

Using Bayesian inference to solve real-world problems requires not only statistical skills, subject matter knowledge, and programming, but also awareness of the decisions made in the process of data analysis. All of these aspects can be understood as part of a tangled workflow of applied Bayesian statistics. Beyond inference, the workflow also includes, for example, iterative model building, model checking, validation and troubleshooting of computational problems, model understanding, and model comparison. Related Bayesian workflow paper https://arxiv.org/abs/2011.01808 and video https://www.youtube.com/watch?v=ppKpwtGy8KQ.

Flexible starting time and contract length (1-3 years). Decent salary, great research community. Helsinki is in the top-10 most liveable cities, and Finland is the world's happiest country. Possibility to spend time with collaborators in New York, Melbourne, or Stuttgart.
Statistician - Climate Science
Sandia National Laboratories
As climate security becomes a higher priority, we are seeking a results-oriented Mathematical Statistician with expertise or interest in earth science applications. The successful applicant will contribute to our interdisciplinary research and help to address novel technical challenges. Potential areas of application may include atmospheric sciences, geoscience and climate sciences to name a few. The ideal candidate will have either a Masters in Statistics (or closely related field) plus one-year related experience or Ph.D. in stated field, and familiarity with statistical programming languages. Desired qualifications include research experience in spatial or spatio-temporal statistics, interest in developing statistical models for the earth sciences and experience collaborating with scientists from a diverse set of backgrounds. Applicants for employment need to be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. Full info available at: https://cg.sandia.gov/psc/applicant/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HRS_CG_SEARCH_FL.GBL?Page=HRS_APP_JBPST_FL&Action=U&FOCUS=Applicant&SiteId=1&JobOpeningId=676876&PostingSeq=1&SiteId=1
Link: https://cg.sandia.gov/psp/applicant/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HRS_CG_SEARCH_FL.GBL?Page=HRS_APP_JBPST_FL&Action=U&FOCUS=Applicant&SiteId=1&JobOpeningId=676876&PostingSeq=1&SiteId=1
Statistician - National Security
Sandia National Laboratories
We are seeking a Mathematical Statistician to join our dedicated and driven team. The successful applicant will contribute to our interdisciplinary research and learn new concepts to address novel technical challenges. The ideal candidate will have a strong mathematical statistics background with either a Masters in Statistics (or closely related field) plus one-year related experience or Ph.D. in stated field, and familiarity with statistical programming languages. Desired qualifications include interest or familiarity with functional data analysis and experience collaborating with scientists from a diverse set of backgrounds. Applicants for employment need to be able to obtain and maintain a DOE Q-level security clearance, which requires U.S. citizenship. Full info available at: https://cg.sandia.gov/psp/applicant/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HRS_CG_SEARCH_FL.GBL?Page=HRS_APP_JBPST_FL&Action=U&FOCUS=Applicant&SiteId=1&JobOpeningId=676875&PostingSeq=1&SiteId=1
Link: https://cg.sandia.gov/psp/applicant/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HRS_CG_SEARCH_FL.GBL?Page=HRS_APP_JBPST_FL&Action=U&FOCUS=Applicant&SiteId=1&JobOpeningId=676875&PostingSeq=1&SiteId=1
Bayesian Modeler, Knowledge Engineer
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Looking for entrepreneurial Bayesian modelers/knowledge engineers loving behavioral & psychometric data for a decision making service… Pre-launch, BIG equity, big players involved. Hit me up 🌞
Link: None
Postdoctoral Scholar – Department of Statistics UCI
University of California, Irvine
The Statistics Department at UC Irvine has a full-time position available for a Postdoctoral Scholar. This position requires a Ph.D. degree in statistics, computer science (machine learning), or mathematics. The position entails performing research in the area of Bayesian analysis, stochastic process modeling, statistical machine learning, computational statistics, and statistical methods in neuroscience. The research involves developing computationally efficient statistical models for neural data analysis.

The appointment is for one year initially (with a flexible starting date) and can be extended. The salary for this position begins at $54,540 but is also contingent on knowledge and experience. The position is dependent upon extramural funding.

Interested applicants should respond by submitting a cover memo, curriculum vitae, and the names and addresses of three references at: https://recruit.ap.uci.edu/JPF06412

Applicants should respond no later than July 10, 2021, for full consideration.

The University of California, Irvine is an Equal Opportunity/Affirmative Action Employer advancing inclusive excellence. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age, protected veteran status, or other protected categories covered by the UC nondiscrimination policy.
Link: https://recruit.ap.uci.edu/JPF06412
Postdoctoral Fellow, University of Michigan
University of Michigan, Ann Arbor
A position for Postdoctoral Fellow is available at the University of Michigan, Mechanical Engineering Department, UQ-SciML Group. The candidate will develop theory and algorithms for Bayesian methods of uncertainty quantification (UQ) and machine learning (ML). Research involves, for example: variational inference, Markov chain Monte Carlo, information divergence estimation, batch and sequential optimal experimental design, reinforcement learning (RL) and inverse RL for sequential Bayesian experimental design, and Bayesian and physics-informed neural networks. These UQ/ML methods will be developed and implemented alongside applications in engineering and science, such as fluid mechanics, material physics, and physically-based biomedicine. Thus, the candidate will work in a collaborative and interdisciplinary environment that intersects statistics, ML, computational science, and engineering physics.

To apply:
Please send your CV, representative publications, and contact information for three references to Prof. Xun Huan (xhuan@umich.edu). Please also include a cover letter describing your specific interest in the position, and skills and experience that relate to this position. Review of applications will begin immediately.

More information can be found at: https://uq.engin.umich.edu/openings/
Link: https://uq.engin.umich.edu/openings/
Assistant Professor – Econometrics and Business Statistics
Melbourne Business School, University of Melbourne
The Melbourne Business School (MBS) seeks to fill a position of Assistant Professor in Econometrics and Business Statistics. Applicants must have a Ph.D. in econometrics, statistics or data science and must demonstrate the potential to publish in top academic journals and achieve excellence in teaching.

Closing soon! Visit the link for more details and submit your application by 30 June 2021.
Link: https://melbournebusinessschool.connxcareers.com/Job/Details/0024bf3aa1604539a47f6d5f7520ec03?isIframe=False
Postdoctoral Associate in Statistical Science
Duke University
The Department of Statistical Science at Duke University is offering a postdoc position under the direction of Prof. Li Ma (http://www.stat.duke.edu/~lm186/).
The position will focus on statistical modeling and method development for complex multivariate data and building scalable computational algorithms.

One research area of particular interest involves developing models and methods for high-dimensional compositional data arising from microbiome sequencing experiments. Another research area involve developing nonparametric models and theory for inference on latent structures and characterizing cross-sample variability in multivariate data. The candidate may work in one or both areas depending on their strength and interest. There will also be opportunities for collaboration with biomedical experts.

Strong background in Bayesian modeling/inference, computing, a genuine interest in tackling practical data analytical challenges in biomedical applications are all considered a plus.

Interested parties should submit a cover letter describing their interests and experiences with regard to this position along with a CV and three references in Academic Jobs Online (https://academicjobsonline.org/ajo/jobs/18694).

To learn about some of the recent projects at Prof. Li Ma’s group, check out the Contributed Presentations given by current members and recent alumni of the group at this conference:

C07: Logistic-tree normal model for microbiome compositions
C12: Dirichlet-tree multinomial mixtures for clustering microbiome compositions
C12: COMIX: Coarsened Mixtures for Calibration of Flow Cytometry Data
C14: Tree boosting for learning probability measures

Link: https://academicjobsonline.org/ajo/jobs/18694
Postdoc in Biostatistics/
Oak Ridge National Laboratory
We are seeking a Postdoctoral Research Associate in the Biostatistics and Multiscale Systems Group in the Advanced Computing for Health Sciences Section of the Computational Science and Engineering Division (CSED). The candidate will work on statistical and applied math problems related to healthcare outcomes using scalable ML/AI. We are specifically seeking a candidate with experience handling multimodal health and community level social and environmental data. The position requires innovative thinking to design and implement machine learning, or algorithmic solutions to real world problems in healthcare and biomedical research.

See link for more information.
Link: https://jobs.ornl.gov/job/Oak-Ridge-Postdoctoral-Research-Associate-AI-and-ML-TN-37830/750044900/
Assistant Professor in Statistics or Applied Probability (Fixed-Term, 3 years) at the University of Nottingham, UK
University of Nottingham
We are looking for an Assistant Professor to deliver high quality teaching and undertake original research of international excellence in Statistics or Applied Probability, complementing and enhancing the current activity of the Statistics and Probability Section. The School of Mathematical Sciences was ranked in the top ten for both research power and grade point average in the Mathematical Sciences in REF 2014. The highly research active and growing Statistics and Probability Section comprises 15 permanent academic staff including the recent recruitment of 3 Professors in Statistics. The Section has research strengths in the broad areas of Bayesian statistics, computational statistics and machine learning, uncertainty quantification, applied probability, and stochastic processes with internationally leading research groups in epidemic modelling and shape and object data analysis. We welcome applications from excellent candidates in any area of Statistics or Applied Probability.

Please see link below for further information (e.g. role profile etc).
Link: https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI144421
Postdoc at Bristol on likelihood free inference
University of Bristol
We have a 20 month post-doc position at the University of Bristol working on novel methods in likelihood-free inference, making use of ideas from neural density estimation and probabilistic programming, with an application to particle physics, working with me and Atılım Güneş Baydin from Oxford computer science. The deadline for applications is 16th July, aiming to start the post in September. Full details are available at:

https://www.bristol.ac.uk/jobs/find/details/?jobId=236534&jobTitle=Research%20Associate

Applications are welcome from candidates with a background in statistics or machine learning. Informal queries about the post are welcome, please contact me at dennis.prangle@bristol.ac.uk.
Link: https://www.bristol.ac.uk/jobs/find/details/?jobId=236534&jobTitle=Research%20Associate
Assistant Professor x3 in Statistics at Lancaster University, UK
Lancaster University
Equivalent to Lecturer in the UK system.
Applications are sought from candidates working in methodological statistics connected with real-world challenges. You should have a proven track record of publishing research work of international quality, and demonstrate potential for being a capable and enthusiastic contributor to the Department’s Statistics teaching. Your role will be an independent academic in the Department, aligned to one of the research groups but following your own research agenda, while also teaching and carrying out academic administration.
The Department provides an environment that aims to meet the individual needs of each member of staff. All new lecturers are provided with mentoring and support from the group as a whole, with a carefully selected group lead taking responsibility for personal development. We are committed to family-friendly and flexible working policies, and seek to promote a healthy work-life balance.
Link: https://hr-jobs.lancs.ac.uk/Vacancy.aspx?ref=A3441
Doctoral candidate for the PhD project "Bayesian sampling design for repeated reliability demonstration"
Physikalisch-Technische Bundesanstalt (PTB)
The Physikalisch-Technische Bundesanstalt (PTB) is the national metrology institute of the Federal Republic of Germany with scientific and technical service tasks. It furthers progress and reliability in metrology for society, the economy, and science.

With a starting date as soon as possible, Department 8.4, Mathematical Modelling and Data Analysis, is looking for a candidate to fill the following position at our Berlin site for a duration of three years:
Doctoral candidate specializing in
statistics, mathematics or a similar subject
Remuneration Group 13 TVöD Bund (85 %), fixed-term contract

Your tasks:
Once hired, you will work in Working Group 8.42 “Data Analysis and Measurement Uncertainty” that develops and applies statistical methods for data analysis. Research in the group is often carried out in collaboration with experimentally oriented working groups at PTB, with industry or with external academic partners.

You work on the PhD project "Bayesian sampling design for repeated reliability demonstration". Your aim is to develop statistical approaches which enable an efficient and flexible surveillance of the quality of populations of measuring instruments. For this purpose (sequential) sampling procedures will be augmented with additional, historical information. You successfully complete the doctoral curriculum at PTB and at the RWTH Aachen University, publish scientific articles and earn a doctorate.

For the full job description please follow the link below.
Link: https://www.ptb.de/cms/en/about-us-careers/careers/bms-stellen/bms-stelle.html?tx_jobmodul_pi1%5Bjob%5D=3911&tx_jobmodul_pi1%5BlistBackPid%5D=11489&cHash=3c368efb943525dd2ee15582137ec6a8
Postdoc in Statistics
Pontificia Universidad Católica de Chile
Dear friends, the Chilean Government is going to open a FONDECYT Postdoctoral Grants Competition soon (July-August 2021). This is a full-time position for 2 or 3 years (depending on the project). Researchers who attained a Doctoral degree as of January 1st, 2018 or later, may apply to this competition. The grant will cover salary (approximately USD 30,600 / year), travel and operational expenses (USD 6,100/year) and installation allowance (USD 4,000 for the 1st year) .

A local researcher at a Chilean university must sponsor the proposal and I would play that role. Therefore, the proposal should be about Longitudinal Models for Complex Data / Spatial Models for Complex Data. The candidates can see my webpage for recent papers and current grants (http://www.mat.uc.cl/~mcastro/public_html/About_Me.html).

Candidates must send the following documents to mcastro@mat.puc.cl ASAP, including:

– Cover letter
– CV
– Publication list
– Summary of research accomplishments and potential research interest.

Please feel free to send this mail to anyone that you think appropriate.

Many thanks in advance,

Mauricio.


Mauricio Castro
Department of Statistics
Pontificia Universidad Católica de Chile

mail 1: mcastro@mat.uc.cl
mail 2: luiscastrocepero@gmail.com
http://www.mat.uc.cl/~mcastro/public_html/About_Me.html

Phone: +562-23541451
Link: http://www.mat.uc.cl/~mcastro/public_html/About_Me.html
Senior Data Scientist, Machine Learning
Zymergen
We are seeking a Sr. Data Scientist with strong Machine Learning experience to join our Experiments and Optimization team. The team builds and deploys ML, data capture, and experimental design tools to accelerate the discovery of novel molecules and materials at Zymergen. As a Sr. Data Scientist, you will work on developing and deploying ML pipelines in close collaboration with lab scientists, computational chemists, statisticians, and software engineers. You will develop cutting edge solutions at the intersection of ML and materials science.

We are open to having this be a fully remote position, and we are flexible on working only part of the week from the office if you prefer.

Learn more about the team by reading this blogpost https://www.zymergen.com/blog/how-machine-learning-is-changing-the-way-we-design-products/

Founded in 2013 and headquartered in the SF Bay Area, Zymergen is a science and material innovation company rethinking biology and reimagining the world. A World Economic Forum Tech Pioneer, Zymergen partners with nature to create never-before imagined materials and products across industries – from agriculture to consumer electronics, personal care to pharmaceuticals, and more. The company’s materials are in use today, creating value for Fortune 1000 companies and major corporations across the globe. Our clients have sold over $1 billion worth of products using Zymergen microbial strains.

Legal authorization to work in the U.S. is required. Zymergen may agree to sponsor an individual for an employment visa now or in the future if there is a shortage of individuals with particular skills for this job.
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.

To learn more and apply, click on the greenhouse link provided at the top of this post.
Link: https://boards.greenhouse.io/embed/job_app?for=zymergen&token=3135664
Statistical modeling scientist
Metrum Research Group
At Metrum Research Group we develop and implement quantitative, data-driven, model-based strategies for knowledge integration and decision support in biomedical research and development. As a scientist on our Statistics team, you will contribute to fighting diseases through an emphasis on Bayesian analysis, causal inference and building models which integrate multiple data sources.
Postdoctoral fellowship in Environmental Health (EH) Biostatistics
University of Rochester
Applications are invited for a postdoctoral fellowship in Environmental Health (EH) Biostatistics in the Department of Biostatistics and Computational Biology at the University of Rochester (UR), funded by an NIEHS T32 training grant. Depending on statistical training, the appointee will develop novel statistical methodology for projects related to EH, or carry out applied statistical analyses for EH-related projects, under the co-mentorship of Biostatistics and EH faculty trainers. Methodological expertise among Biostatistics faculty trainers includes Bayesian MCMC methods, models for multiple outcomes, latent variable models, measurement error, missing data, causal inference, survival analysis, clustering, statistical genomics, molecular systems biology, and bioinformatics.

The specific area of methodological development or applied analysis may be based in part on the trainee’s interests, and may be motivated by ongoing EH research at UR, such as studies of the effects of exposure to air pollution, metals, endocrine disruptors, pesticides, shale gas (fracking) or stress on pregnancy outcomes, reproduction, immune function, neurodevelopmental disorders, cognitive outcomes, or gene expression pathways. The appointee will also receive further training in biostatistics and toxicology, and be involved in collaborative work with EH researchers. Interested trainees will have the opportunity to gain experience in community engaged research related to understanding and addressing environmental health problems.

The candidate should plan to start in fall 2021, but a later start date will also be considered. Applications will be accepted until Sept 1 or until filled.
Link: https://www.urmc.rochester.edu/biostat/employment/t32-postdoc.aspx
Postdoctoral Research Fellow
King Abdullah University of Science and Technology (KAUST)
One postdoctoral fellowship in statistics is currently available in the Stochastic Processes and Applied Statistics research group at KAUST.

The general research area of the position is spatio-temporal statistics and possible research topics include: Construction of non-Gaussian models based on stochastic partial differential equations (SPDEs) and the analysis of their properties; Numerical discretization methods of SPDEs and their use for computationally efficient Bayesian inference; Multivariate random fields; Spatio-temporal models; Random fields on manifolds and graphs; Applications in medical imaging and environmental sciences.

The position comes with a very competitive tax-free salary as well as free housing and free health insurance. The starting date is flexible, and the postdoctoral appointments are renewable annually for up to three years.

Applicants must hold a PhD degree in statistics, applied mathematics, or a related field. Successful candidates must have strong analytical skills and a solid knowledge of scientific programming. Further, experience in one or more of the following areas is required: Spatial and spatio-temporal statistics; Stochastic processes; Stochastic partial differential equations; Numerical solutions of PDEs and SDEs; and Uncertainty quantification. The candidate will be expected to work in a collaborative research environment with PhD and MS students within the group.
Link: http://stochproc.kaust.edu.sa
Senior Statistician
NORC at the University of Chicago
NORC at the University of Chicago is an objective, non-partisan research institution that delivers reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions. Since 1941, our teams have conducted groundbreaking studies, created and applied innovative methods and tools, and advanced principles of scientific integrity and collaboration. Today, government, corporate, and nonprofit clients around the world partner with us to transform increasingly complex information into useful knowledge.

The Statistics and Data Science Department implements state-of-the-art statistical methods and develops innovations to deliver reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions for NORC clients. In collaboration with all NORC subject area departments, the Statistics and Data Science Department provides leadership along the project life cycle for study design, data collection, analysis, and dissemination of results, and also conducts its own research. The department is a leader in designing and implementing rigorous, efficient methods for sampling from populations and weighting resultant survey data. The department provides expertise and leads NORC strategy on the use of a broad range of methods for the analysis of primary and secondary data, including Bayesian analysis, data linkage and statistical matching for combining multiple data sources, data quality assessment, differential privacy, imputation, machine learning, small area estimation, statistical disclosure limitation, survival analysis, visualization, and efficient and reproducible workflow development.
Link: https://careers.norc.org/en-us/job/497129/senior-statistician
Research Methodologist
NORC at the University of Chicago
NORC at the University of Chicago is an objective, non-partisan research institution that delivers reliable data and rigorous analysis to guide critical programmatic, business, and policy decisions. Since 1941, our teams have conducted groundbreaking studies, created and applied innovative methods and tools, and advanced principles of scientific integrity and collaboration. Today, government, corporate, and nonprofit clients around the world partner with us to transform increasingly complex information into useful knowledge.

The Research Methodologist would be based in the Methodology and Quantitative Social Sciences department, which provides expertise on state-of-the-art methodologies that lead to insights about our society and inform decision-making. We seek quantitative social scientists, methodologists and data scientists to provide expertise in methods to advance social science research in areas such as data gathering, evaluation, and implementation. Examples include causal inference methods applied to data obtained from randomized experiments or gathered from observational sources; assessing measurement properties (e.g., psychometrics) of new measures; machine learning/natural language processing; network methods; and analysis of clustered data (e.g., multilevel data, spatial modeling, etc.). We are also engaged in using existing and emerging data sources of importance for NORC projects; harnessing novel data sources and technologies to improve data gathering; assessing and improving data quality; understanding the cognitive processes informing the user experience for survey respondents; designing instruments for multiple modes; and developing and testing novel techniques to enhance recruitment and retention of study participants.

Please see the linked job posting for further details.
Link: https://careers.norc.org/en-us/job/497206/research-methodologist
Postdoctoral fellow in biomedical data science
The University of Hong Kong
We are looking for a postdoctoral fellow to work in biomedical data science, with a focus on single-cell omics data. The specific projects and aims can be defined together with the Principal Investigator (Dr Yuanhua Huang). Potential directions include statistical modelling of somatic mutations for cancer evolution, integrative analysis of single-cell multi-omics data, and computational methods for dissecting spatial transcriptomics data.

Applicants should have a PhD degree (or nearly finishing) from a quantitative field, including but not limited to statistics, computational biology, bioinformatics, and computer science. Experience in working with statistical modelling and/or genomic sequencing data analysis is preferred. Those with less experience but with a strong interest in biology are also encouraged to apply. Please contact Dr Huang if you have any questions.

Outstanding candidates are encouraged to try the generously supported Presidential Postdoctoral Fellowship.
Link: https://web.hku.hk/~yuanhua/
Research Fellow in Data Science
University of Western Australia
On July 1st 2021, the Transforming energy Infrastructure through Digital Engineering (TIDE) Research Hub kicked-off a five-year research program. This is an outstanding opportunity for a self-driven researcher to enhance their career, develop strong technical skills, and expand their network by working as part of a large scale, international, multi-disciplinary research group in order to solve industry-focussed problems.

To be considered for this role, you will demonstrate:

* A PhD specialising in Bayesian inference and uncertainty quantification, or a closely related field.
* Demonstrated experience with working in interdisciplinary teams.
* Willingness to interact and/or work with the offshore engineering industry.
* Experience preparing manuscripts for publication and giving presentations at conferences, with a strong track record relative to opportunity.
* An ability and willingness to direct and supervise students.
Link: https://external.jobs.uwa.edu.au/cw/en/job/507196?lApplicationSubSourceID
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