Lecturer/Senior Lecturer in Statistics, Data Science, Stochastic Modelling

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School of Mathematical Sciences
University of Adelaide

Closing date: 1st August 2021

(Level B, Lecturer) $100,933 to $119,391 or (Level C, Senior Lecturer) $123,075 to $141,537 per annum plus an employer contribution of up to 17% superannuation may apply. 

Three-year fixed term position available from December 2021.  On conclusion of the three-year term, the position may be converted to a continuing position under the provisions of the University’s Enterprise Agreement.  

Two full-time positions are available.

The University of Adelaide is seeking to grow the statistics, data science, and stochastic modelling team in the School of Mathematical Sciences. This is an opportunity for a highly motivated researcher and committed educator to join a School that is a leader in pedagogical innovation and received the highest possible rating of research quality in the mathematical sciences overall and in each of its disciplines in the two most recent ERA assessments.

The School has identified data science, broadly construed, as one of its strategic priorities. We are seeking an enthusiastic colleague to work with us to expand our research and educational offerings in statistics, data science, and stochastic modelling. Willingness to engage with industry would be an asset. 

The School is strongly committed to increasing the diversity of its staff and students. These two available positions are directed at applicants who are able to contribute to the diversity of the School community.

For more information and to apply, click here.

Postdoctoral Research Assistant 

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Department of Statistics and the Wellcome Centre for Human Genetics
University of Oxford

Closing Date:30th July 2021

Grade 7: £32,817 – £40,322 p.a. 

We invite applications for a postdoctoral research assistant to develop predictive models for how DNA sequences impact regulatory networks, and apply these models to new single-cell datasets including for both gene expression, and chromatin accessibility (openness) during meiosis. The successful candidate will create new techniques integrating information from genomic DNA sequences, to perform mixture decomposition of sparse data matrices, and non-linear prediction, among other goals. We anticipate the resulting methods will be widely applicable to provide a technique for identifying the role of mutations, for example those identified in genome-wide association studies, in impacting gene expression in general. The postholder will work jointly at the Department of Statistics and the Wellcome Centre for Human Genetics. The post holder will join Oxford’s leading genomics research community, and the project may involve international collaboration and potential visits to collaborating groups.

The successful candidate will hold or be close to completion of a PhD/DPhil in a relevant quantitative scientific discipline, for example statistics, machine learning, mathematics, statistical or population genetics, or related disciplines. They also should have experience in developing and applying novel statistical methods, and low-level programming. Experience in analysing high-dimensional datasets, for example in computational statistics, machine learning, is highly desirable. They should have a strong interest in biological problems, genetics and/or genomics, but previous experience is not essential.

Queries about this post should be addressed to: Professor Simon Myers at myers@stats.ox.ac.uk.

This post is fixed-term until 10 September 2023.

Only applications received before 12.00 midday on 30 July 2021 will be considered. Interviews will be held on 25 August 2021.

For more information and to apply, click here.

Postdoctoral Research Assistant

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Department of Statistics and the Wellcome Centre for Human Genetics
University of Oxford

Closing Date: 30th July 2021

Grade 7: £32,817 – £40,322 p.a 

We invite applications for a PDRA to develop statistical methods to study differences in healthy phenotypes and disease risks between human populations, and apply these to Biobank-scale datasets. This work aims to develop improved approaches to genetic prediction of disease risk by combining information among groups and/or modelling the evolution of traits through time.

The post holder will develop methods to understand whether strong differences in identified genetic predictors in different human populations, and lack of transferability of polygenic scores among human groups, reflect mainly genetic or environmental differences. They will also map the origins of disease-causing rare variants in time, and at fine geographic scales for example within regions of the UK, in order to understand the applicability of rare variant discoveries to other regions or populations. Leveraging genealogical approaches previously developed within the group represents a natural start-point for this project, but it will also be essential to integrate functional information and to leverage large-scale data on both phenotypes and variation, for datasets incorporating a range of ancestries. The UK Biobank and Genomics England data, in which we have ongoing work, provide two important examples.

This position is based jointly within the Department of Statistics and the Wellcome Centre for Human Genetics. The post holder will join Oxford’s leading genomics research community, and the project may involve international collaboration and potential visits to collaborating groups.

The successful candidate will hold or be close to completion of a PhD/DPhil in a relevant quantitative scientific discipline, for example statistics, machine learning, mathematics, statistical or population genetics, or related disciplines. They also should have experience in developing and applying novel statistical methods, and low-level programming. Experience in analysing high-dimensional datasets, for example in computational statistics, or machine learning, is highly desirable. They should have a strong interest in biological problems, genetics and/or genomics, but previous experience is not essential.

Queries about this post should be addressed to: Professor Simon Myers at myers@stats.ox.ac.uk.

This post is fixed-term until 10 September 2023. Only applications received before 12.00 midday on 30 July 2021 will be considered. Interviews will be held on 25 August 2021.

For more information and to apply, click here.

Lecturer in Mathematics

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University of Sydney
School of Mathematics and Statistics

Closing Date: 13th June 2021

We are currently seeking to appoint an accomplished academic to the position of Lecturer in Mathematics. To succeed, you will be a talented and well-qualified mathematician with a passion for teaching and research expertise in an area that strengthens the school’s profile and align with the research interests of SMRI’s director   Professor Geordie Williamson. This includes, but is not limited to algebra, geometry and representation theory. In particular, researchers with background in geometric representation theory, algebraic geometry or homotopy theory are particularly encouraged to apply. You will need to have appropriate skills and qualifications as outlined in the position description, including a PhD in Mathematics.

If appointed, you will be expected to undertake duties consistent with an appointment at the Lecturer level (Level B) on the Australian academic scale. This will include: publishing scholarly papers in international peer-reviewed journals and presenting at conferences; supervising undergraduate and postgraduate students; teaching a range of courses to undergraduate students; and applying for external funding.

For more information and to apply, click here.

Lecturer/Senior Lecturer in Data Science

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University of Sydney
School of Mathematics and Statistics

Closing Date: 4th July 2021

The University of Sydney is welcoming applications for a Lecturer/Senior Lecturer in Data Science to join leading experts at the School of Mathematics and Statistics, within the Faculty of Science. We are one of the largest mathematical sciences schools in Australia, and the University of Sydney is the only Australian university to have received the highest rating of 5 out of 5 for research in the mathematical sciences in every Australian Research Council Excellence in Research for Australia assessment to date.

As a Lecturer/Senior Lecturer in Data Science you will have the opportunity to make a significant contribution to teaching and learning design, delivery, and evaluation while continuing to build your research contribution, expertise and impact. We are welcoming applicants from different research backgrounds who can bring their own research agenda, complementing the Schools’ current research foci, whilst benefiting from our supportive community of world-class mathematicians and statisticians. We invite applicants with research strengths in the intersection between Data Science and Mathematics or Statistics. This includes, but is not limited to, topics such as statistical machine learning, mathematical foundations of machine learning, computational statistics, information theory, information geometry, statistical natural language processing, topological data analysis,  Bayesian inference, and research areas combining mathematical modelling, computational statistics, and data analysis.

For more information and to apply, click here.

Lecturer/Senior Lecturer in Statistics

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University of Sydney
School of Mathematics and Statistics

Closing Date: 4th July 2021

The University of Sydney is welcoming applications for a Lecturer/Senior Lecturer in Data Science to join leading experts at the School of Mathematics and Statistics, within the Faculty of Science. We are one of the largest mathematical sciences schools in Australia, and the University of Sydney is the only Australian university to have received the highest rating of 5 out of 5 for research in the mathematical sciences in every Australian Research Council Excellence in Research for Australia assessment to date.

As a Lecturer/Senior Lecturer in Data Science you will have the opportunity to make a significant contribution to teaching and learning design, delivery, and evaluation while continuing to build your research contribution, expertise and impact. We are welcoming applicants from different research backgrounds who can bring their own research agenda, complementing the Schools’ current research foci, whilst benefiting from our supportive community of world-class mathematicians and statisticians. We invite applicants with research strengths in the intersection between Data Science and Mathematics or Statistics. This includes, but is not limited to, topics such as statistical machine learning, mathematical foundations of machine learning, computational statistics, information theory, information geometry, statistical natural language processing, topological data analysis,  Bayesian inference, and research areas combining mathematical modelling, computational statistics, and data analysis.

For more information and to apply, click here.

Postdoctoral positions in Mathematics and Stochastics

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Aarhus University
Department of Mathematics

Closing Date: 1st August 2021

The Department of Mathematics at Aarhus University, Denmark, a top 100 University, is seeking top early-career researchers for a number of attractive one to three year postdoctoral positions within Mathematics and Stochastics.

The positions are open from January 1st 2022.

Applicants in all areas of mathematics and stochastics covered by the research groups of the department will be considered. For an overview of the research areas covered by the department, see the home page for the Mathematics Section and for the Stochastics Section. In particular, there will be postdoc stipends available in the areas listed here:

https://math.au.dk/om/ledige-stillinger/postdoc/
The employment period for each of the available positions can be found via the link above.

When applying, you will be asked to indicate, which – if any — of the areas listed on the page above are of interest to you. The page may be updated with new areas up until the deadline for application. The indication of which research areas you are interested in at the time of application, does not automatically exclude you from being taken into consideration for positions in the other research areas available at the time of application, including research areas that may be added later. 

For more information and to apply, click here.

Postdoctoral Research Fellowship in Causal Inference and Causal Machine Learning motivated by Health Applications

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University of Oxford
Department of Statistics

Closing Date: 25th June 2021

Grade 8: £41,526 – £49,553 p.a 

Applications are invited for a full-time 3-year Postdoctoral Research Fellowship in Causal Inference and/or Causal Machine Learning motivated by Health Applications. The project is part of a wider collaboration with Novo Nordisk and the University of Manchester within a network of researchers that includes UC Berkeley and Copenhagen. The postholder will research novel statistical and machine learning methodologies that have the potential to improve causal inference and prediction in large scale systems, with a particular emphasis towards understanding the co-occurrence of diseases within individuals.

You will develop research questions and conduct individual research, utilising access to detailed real-world quantitative data from a variety of sources to motivate new methodologies. You will develop and implement novel scalable methods for causal inference and learning, and regularly write research articles and publish outcomes of research in relevant high-profile international journals and conferences. There is significant funding to support attendance at international conferences and travel visits across the research network mentioned above. You will provide guidance to junior members of the research group including PhD students. You will act as a source of information and advice to other members of the group on methodologies or procedures and represent the research group at conferences, external meetings, and seminars.

We are seeking an exceptional candidate who holds (or is close to completing) a PhD in Statistics, Machine Learning, or a related field, together with relevant experience in probabilistic models and/or causal inference. You will possess sufficient specialist knowledge in scalable probabilistic models and can manage your own academic research and associated activities. Previous experience of contributing to publications and presentations is essential.

This post is fixed-term up to three years, in the first instance.

Only applications received before 12.00 midday on 25 June 2021 will be considered. Interviews will be held on 7 July 2021.

Contact Email :  HR@stats.ox.ac.uk

For more information and to apply, click here.

Postdoctoral Research Associate in Mathematics (Level A)

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University of Technology Sydney
School of Mathematical and Physical Sciences

Closing Date: 28th June 2021

An exciting opportunity exists for Postdoctoral Research Associate (Level A) to conduct research in a collaborative research team based within the Faculty of Science at UTS.

This position is part of a research project funded by the ARC Discovery Project “Geodetic groups: foundational problems in algebra and computer science” awarded to Professor Murray Elder (UTS), Dr Adam Piggott (Australian National University) and Professor Volker Diekert (University of Stuttgart).

The role will carry out mathematical research, prepare, and present results in papers and conferences, co-supervise undergraduate and graduate research students, and be involved in outreach and mentoring activities. You will bring to the position expertise in geometric or computational group theory, combinatorics, and/or theoretical computer science.

Additionally, you will be expected to support the activities of the research team and apply for independent research fellowship or funding.

Skills and Attributes

  • Ability to undertake original research, as evidenced by timely and high-quality outputs.
  • Willingness to contribute to seek research funding from external sources.
  • Provide quality research supervision, where eligible, for Higher Degree Postgraduate and Honours students.
  • Demonstrated capacity to work independently and as part of a team.
  • Excellent oral and written communication skills.
  • Ability to critically think and independently.

Qualifications and Experience

Mandatory

  • PhD in geometric group theory, combinatorics, theoretical computer science or related areas.
  • Excellent written and oral communication skills in English.
  • Demonstrated organisational skills, time management and ability to work to deadlines.
  • Demonstrated problem solving abilities and analytical skills.
  • The ability to work independently as well as collaboratively as a member of a team.

Preferred

  • Publications in geometric group theory and/or formal language theory, automata, rewriting systems.
  • Proficient programming skills.
  • Experience with computer algebra systems such as GAP.

Please refer to the Position Description for further information. Only those applications submitted via the UTS online recruitment system will be accepted.

Apply online here.

OPTIMA Postdoctoral Research Fellow

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University of Melbourne

Closing Date: 14th June 2021

The Research Fellow is expected to conduct world-class research and provide training for research students working in industrial optimisation as a key appointee in a newly established ARC Training Centre in Optimisation Technologies, Integrated Methodologies and Applications (OPTIMA). The research program involves a focus on model-based and black-box optimisation methodologies of relevance to a broad range of industry partner optimisation challenges. A multidisciplinary approach is expected, drawing from techniques developed in mathematics, computer science, statistics, engineering, and economics.

We invite applications from Level A and Level B candidates. Although advertised full-time, part-time working hours and flexible conditions will be considered.

For more information and to apply, click here.