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.

Symmetry in Newcastle seminar – Monday 24th May 2021

Symmetry in Newcastle seminar is here again! The confirmed speakers for next Monday are Libor Barto, Charles University in Prague, and Zoe Chatzidakis, CNRS – ENS. Feel free to grab a beverage appropriate for your respective timezone (we won’t judge) and join us for a friendly chat during the break!

The talks will be recorded and made available on our YouTube channel https://tinyurl.com/zerodimensionalgroup and our website https://zerodimensional.group/. The running times of the talks, titles and abstracts are as follows

16:30 – 17:30 AEST (06:30 – 07:30  UTC) Libor Barto
17:30 – 18:00 AEST (07:30 – 08:00  UTC) Break and chat
18:00 – 19:00 AEST (08:00 – 90:00  UTC) Zoe Chatzidakis

Speaker: Libor Barto (Charles University in Prague)
Title: CSPs and Symmetries

Abstract:
How difficult is to solve a given computational problem? In a large class of computational problems, including the fixed-template Constraint Satisfaction Problems (CSPs), this fundamental question has a simple and beautiful answer: the more symmetrical the problem is, the easier is to solve it. The tight connection between the complexity of a CSP and a certain concept that captures its symmetry has fueled much of the progress in the area in the last 20 years. I will talk about this connection and some of the many tools that have been used to analyze the symmetries. The tools involve rather diverse areas of mathematics including  algebra, analysis, combinatorics, logic, probability, and topology.

Speaker: Zoe Chatzidakis (CNRS – ENS)
Title: A new invariant for difference fields

Abstract:
If (K,f) is a difference field, and a is a finite tuple in some difference field extending K, and such that f(a) in K(a)^{alg}, then we define dd(a/K)=lim[K(f^k(a),a):K(a)]^{1/k}, the distant degree of a over K. This is an invariant of the difference field extension K(a)^{alg}/K. We show that there is some b in the difference field generated by a over K, which is equi-algebraic with a over K, and such that dd(a/K)=[K(f(b),b):K(b)], i.e.: for every k>0, f(b) in K(b,f^k(b)).
Viewing Aut(K(a)^{alg}/K) as a locally compact group, this result is connected to results of Goerge Willis on scales of automorphisms of locally compact totally disconnected groups. I will explicit the correspondence between the two sets of results.
(Joint with E. Hrushovski)

See the website for Zoom details.

Nominations for AustMS Medal, Gavin Brown Prize, and George Szekeres Medal due 21st May

This is a REMINDER that nominations for the 2021 Australian Mathematical Society Medal, the Gavin Brown Prize, and the George Szekeres Medal close on 21st May 2021. Nominations should be uploaded at http://journal.austms.org.au/ojs/index.php/AMPA/. Nominators should receive an acknowledgement of the nomination: if this is not received, please contact the respective Committee Chair (see below). Nominations will not be automatically rolled over from previous years.

For further details, see the Awards & Grants page or the March Gazette.

Postdoctoral Research Associate in Mathematics (Level A)

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.