Lecturer in Mathematics

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.

PhD opportunity in multi-scale models in immuno-epidemiology

La Trobe University
Department of Mathematics and Statistics

Closing Date: 30th June 2021

We seek expressions of interest from prospective students to undertake a PhD in the research area: multi-scale models in immuno-epidemiology. The spread of a pathogen (for example, a virus or bacteria) through a population is a multi-scale phenomena, influenced by factors acting at both the population and within-host scales. At the population scale, transmission is influenced by how infectious an infected host is. Infectiousness in turn depends on the balance between pathogen replication within the host and immune/drug control mechanisms.  This project aims to develop new mathematical frameworks for simultaneously modelling these two scales. This will provide a platform for the rigorous study of complex biological interactions – such as the emergence and combat of drug-resistance – that shape society’s ability to control infectious diseases in human, animal and plant systems.

This PhD is funded by an Australian Research Council Discovery Project led by Prof James McCaw and A/Prof Nic Geard at the University of Melbourne, and Dr Rebecca Chisholm at La Trobe University. The successful applicant will be based at La Trobe Bundoora Campus and work closely with all investigators.

Graduates with a strong background in applied mathematics and with strong programming skills in either Python, Matlab, or R are encouraged to apply. Experience in infectious disease modelling is preferred, but not essential.

Further details: https://www.latrobe.edu.au/scholarships/mathematical-models-in-immuno-epidemiology-phd-scholarship

How to apply

  • review details on how to apply for candidature at La Trobe University
  • contact Dr Rebecca Chisholm (r.chisholm@latrobe.edu.au), with any enquiries or to express an interest in the project.
  • when you have received in-principle agreement for supervision, complete and submit your application by 30 June 2021 for admission into La Trobe’s PhD program, indicating you wish to be considered for this scholarship on the application.

The University will carefully review your application and consider you for this scholarship. You will be advised of an outcome in July 2021.

Members are encouraged to nominate for the Australian Mathematical Society’s Teaching Excellence Awards

The AustMS annual Award for Teaching Excellence and the annual Award for Teaching Excellence (Early Career) have been established to encourage excellence in mathematics teaching in higher education. The AustMS Award for Teaching Excellence and Award for Teaching Excellence (Early Career) aim to recognise and reward outstanding contribution to teaching and student learning in the mathematical sciences at the tertiary level. With these awards the AustMS recognises the importance of quality of mathematics teaching and the impact it has on the training of a future mathematics workforce. Progressive teaching is essential to maintaining high standards across service courses for other disciplines, where high-quality mathematics teaching is of key importance.

Each year a Teaching Excellence Award and a Teaching Excellence Award (Early Career) will be presented at the Annual Meeting, with the prize money for each award set at $1000 per annum. Awardees will be invited to give a presentation on their work at the Annual Meeting and write a short classroom note for the Gazette. For more details see this page or email Chris Tisdell for clarification.

Nominations for these awards will close on 31 August 2021.

Applications for the 2021 Alf van der Poorten Travelling Fellowship now close on 16th June (closing date has been extended).

Prospective applicants should visit the Society’s web site here for an application template before submitting an application electronically to the selection committee before 16 June. The Alf van der Poorten Travelling Fellowship, of up to $10,000, is offered to early-career researchers who have obtained their PhD in pure mathematics from an Australian university.

To be eligible to apply, a candidate must have qualified for their PhD within five years of the closing date, allowing for career interruptions, and they cannot have previously been awarded the Alf van der Poorten Fellowship. Applicants must have been members of the Society for the consecutive twelve-month period immediately prior to the date of application. (Back dating of membership to the previous year is not sufficient.)

Call for Special Sessions at AustMS 2021, University of Newcastle, December 2021

The 65th Annual Conference of the Australian Mathematical Society will be held at the University of Newcastle, 6-10 December 2021. We warmly invite proposals for special sessions at this year’s edition of the conference. We hope to have a very good representation of our mathematical strengths in Australia, so please come forward in proposing a special session in your area of research or education.

If you wish to run a special session, please submit your proposal here. The deadline for submision of proposals is 20 June 2021.

For a list of special sessions at previous AustMS conferences, please see:

Best wishes, Florian Breuer (AustMS 2021 Conference Director)

Lecturer/Senior Lecturer in Data Science

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

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

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

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.

AustMS travel awards and Maryam Mirzakhani Award round 14

The Society has a series of regular awards to support women mathematicians. Two of these are the Cheryl Praeger Travel Award and the Maryam Mirzakhani Award. The most recent awardees are as follows.

Cheryl Praeger Travel Award: two funded applications
1. Adriana Zanca for the requested $1,000 (domestic travel) for a research visit to Queensland University of Technology (QUT), Brisbane  
2. Nargiz Sultanova for the amount of $477 (or the AUD amount equivalent to 365 USD)  for the SIAM Conference on Optimization (international conference, to be held virtually).
 
Maryam Mirzakhani Award successful applicant Maud El-Hachem.

The committee has also proposed Ayreena Bakhtawar for honourable mention. She came in second for the award both in 2020 and 2021. 

A little bit about this year’s MM awardee: 

Maud came to her postgraduate studies in applied mathematics with a background in computer science.  Her undergraduate training and Master’s thesis involved the development of computational algorithms for approximating gradient operators using novel GPU approaches.  Given Maud’s background in computer science and numerical methods, her PhD program focuses on the analysis (formal asymptotics and numerical methods) to study partial differential equation models of invasion that are often used in mathematical biology.  

Maud’s research focuses on comparing classical models, such as the well-known Fisher-Kolmogorov model, with more recent approaches that re-cast these models as moving boundary problems.  This work seeks to overcome a key limitation of the Fisher-Kolmogorov model which, when non-dimensionalised, leads to travelling wave solutions with a positive wave speed, c > 2.  This means that standard analysis neglects slower travelling wave solutions with c < 2.  These slow travelling wave solutions are routinely disregarded on the grounds of being non-physical owing to arguments that arise in the phase plane.  One of the limitations of traditional mathematical approaches to understand invasion is that the underlying biology is highly idealised, and a consequence is that travelling wave solutions with c < 2 are completely disregarded.  Maud’s work has carefully compared the classical application of the Fisher-Kolmogorov model with the more recent approach of studying the same partial differential equation reformulated with a moving boundary.  This reformulated problem, that Maud has called the Fisher-Stefan model, allows us to study travelling wave solutions with arbitrary speed.  This includes travelling wave solutions with c < 2, and even travelling wave solutions with c < 0, which Maud has called a receding travelling wave.  Maud’s work has been published in the Bulletin of Mathematical Biology, Physica D: Nonlinear Phenomena and Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.