Lecturer/Senior Lecturer in Pure Mathematics @La Trobe

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Location: La Trobe University, Bundoora campus; Department of Mathematical and Physical Sciences
Employment Type: Continuing (Full Time)
Remuneration:  Level B or Level C Academic Appointment
Closing Date: 17 September 2023
Job no: 564041

About the position

This position is located in the Department of Mathematical and Physical Sciences, part of the School of Computing, Engineering and Mathematical Sciences in Melbourne (Bundoora) campus. The School has three departments: Computer Science and Information Technology, Engineering, and Mathematical and Physical Sciences on both Melbourne (Bundoora) and Bendigo campuses.

The Department of Mathematical and Physical Sciences is comprised of active teaching and research staff across the broad disciplines of applied mathematics, pure mathematics, statistics, and physics. The Department offers undergraduate majors in mathematics, statistics, data science, and physics, and also provides many important subjects that are undertaken by students from a diverse range of courses and disciplinary backgrounds (eg. engineering, life sciences, education). Several members hold national and other teaching awards. The Australian Research Council’s Excellence in Research for Australia (ERA2018) ranks the Department’s mathematical sciences as ‘above world standard’, and physical sciences research as ‘well above world standard.’

Reporting to the Head of Department of Mathematics and Physical Sciences a Level B and/or Level C teaching and research academic is expected to develop curriculum, teach and/or undertake research and/or other scholarly work relevant to the development of their discipline or professional field.

A selection of your duties will include:

  • Contribute to cross-disciplinary teaching development and delivery across the Department and School as required.
  • Design, coordinate and teach subjects and courses which provide a high-quality learning experience in the areas of mathematics and data science that engages undergraduate, honours and postgraduate students.
  • Design innovative and effective curriculum which reflects developing best practice nationally and internationally, utilising various methodologies including online and blended learning.
  • Conduct and lead innovative and high impact research in the area of pure mathematics and produce conference and seminar papers and publications resulting from that research.
  • Supervise Higher Degree by Research (HDR), honours and postgraduate students.

Skills & Experience

  • Completion of a PhD or equivalent accreditation and standing recognised by the University/profession as appropriate for the relevant discipline area.
  • Demonstrated effectiveness in curriculum development and teaching with a commitment to excellence in teaching.
  • Demonstrate ability to participate/lead industry/government engagement and/or relevant research.
  • Strong record of research publication, with appropriate evidence of quality and impact.

Please refer to the Position Description for other duties, skills and experience required for this position.

Benefits

  • 17% employer contributed superannuation
  • On site child care facilities
  • Flexible work arrangements
  • Discounts for staff and their family members to study a range of La Trobe courses

For more information and to apply, please visit https://careers.pageuppeople.com/533/caw/en/job/564041/lecturersenior-lecturer-pure-mathematics.

Position Enquiries: Dr Narelle Brack, Head of Department, Department of Mathematical and Physical Sciences, School of Computing, Engineering and Mathematical Sciences, Email: n.brack@latrobe.edu.au, Phone: (03) 9479 3808

Recruitment Enquiries: Vicki Stavrou, Senior Talent Acquisition Business Partner, Email: v.stavrou@latrobe.edu.au, Phone: (03) 9479 5191

Scholarship in Data Science @Curtin

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Closing date: 25 August 2023
Campus: Curtin University; Centre for Optimisation and Decision Science
Remuneration: $60,000 – $70,000 per annum
Status: 3 years
Title: Dynamics-driven operator splitting methods for data science, machine learning, and engineering problems

In data science, machine learning, and engineering, many problems take the form of finding a solution that minimizes a cost, subject to constraints on allowable solutions. Some examples of costs include expected financial losses, model prediction errors, and energy used. Some examples of constraints include resource limitations, minimum requirements on what is produced, and so forth.

These problems are solved with operator splitting methods, a modern class of non-linear optimisation algorithms that allow the constraint structure and cost structure to be treated as two components of a single unifying function. These algorithms were independently discovered by mathematicians working on physics and imaging problems, and they have been developed and improved with the powerful machinery of convex analysis.

For many important problems, we desire to make these algorithms go faster, either to find solutions within the maximum time allowable (for example: balancing power flow in electricity grids) or to make better data science models computationally tractable for large data sets. Researchers have recently turned to studying the dynamical systems associated with operator splitting methods. This research is allowing us to prove results in nonconvex settings and build new algorithms. Dr. Scott Lindstrom recently introduced a meta-algorithm that uses operator dynamics to suggest alternative algorithm updates. The intent of this meta-algorithm is to solve surrogates for something called a Lyapunov function, which is an object that describes the dynamics. This meta-algorithm has already become state-of-the-art for finding wavelets with structural constraints (an imaging sciences problem).

Scientific Aims

The scientific aim of this project is to identify classes of problems in data science, machine learning, and engineering for which meta-algorithms—such as the one described above—may be deliver superior performance. The approach will be multi-faceted, combining both computational experiment and rigorous proof. The results will be communicated in articles and submitted to peer-reviewed publications.

Upskilling Aims

The upskilling aims for the selected candidate are as follows (in no particular order). The candidate will build expertise in the algorithms that make it possible to solve many modern data science models and engineering problems, understanding both how the algorithms are designed, how geometry informs model selection, and what the outstanding challenges are. At the project’s completion, the candidate will be competent to rigorously conduct both experimental and theoretical mathematics research, and to communicate the results of their discoveries to others in the field.

In the literature review component, you will learn the fundamental theory—convex analysis—of operator splitting and learn how operator splitting algorithms are formulated for solving various classes of problems. Some examples of the types of problems you will study are as follows: (1) least absolute deviations for outlier-resistant linear regression (a data science modelling problem), (2) progressive hedging for maximizing expected earnings (a finance problem), (3) computation of a one-norm centroid (a statistics problem), and (4) phase retrieval (a signal processing problem).

In the experimental component, you will apply Lyapunov surrogate methods to solve those problems. You will build performance profiles, which are visualizations that allow researchers to compare the speeds of different algorithms.

In the theoretical component, you will formally analyse the dynamical systems associated with operator splitting methods when they are applied to these problem classes. Particular emphasis will be placed on the duality of algorithms; duality is a fundamental concept in convex analysis.

You will document and communicate the findings in written articles.

Context

As described in the overview, in the here and now, faster operator splitting methods will allow us to obtain better solutions to important problems in data science and energy. On a ten year horizon, this research advances an emerging new paradigm in problem solving, where artificial intelligence will observe an algorithm’s performance and suggest on-the-fly parameter adjustments and alternative updates for the iterates. Finally, the project builds fundamental knowledge in the mathematical sciences and equips the selected candidate with a skill set of extreme contemporary demand.

To apply

For more information, please copy and paste the following link into your web browser: http://staff.curtin.edu.au/Scholarship/?id=6730

Associate Lecturer/Lecturer in Mathematics or Physics @UQueensland

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Location: The School of Mathematics and Physics, University of Queensland
Status: full-time (100%), fixed-term up to 2 years
Remuneration: (Level A) $74,308.68–$99,426.59 or (Level B) $104,579.67–$124,187.99; plus super of up to 17%
Closing date: 21 July 2021
Reference: R-27253-2

About this opportunity

This is an exciting opportunity in the School of Mathematics and Physics for an Indigenous Associate Lecturer/Lecturer to focus their efforts on developing their expertise and emerging academic profile in the area of Mathematics, Statistics, Mathematical Data Science or Physics. At this level, it is expected that the successful candidate will gain or develop their experience in teaching and course coordination, begin to establish an independent research profile, and contribute to service and engagement roles and activities.

Please view the Candidate Information Booklet below for the key responsibilities.
This is a teaching & research academic position. Further information can be found by viewing UQ’s Criteria for Academic Performance.
This is a full-time (100%), fixed-term position for up to 2 years, at Academic Level A or B depending on experience.

The full-time equivalent base salary at Level A will be in the range of $74,308.68–$99,426.59 plus super of up to 17%. The total FTE package will be in the range of $86,941.16–$116,329.11.

The full-time equivalent base salary at Level B will be in the range of $104,579.67–$124,187.99 plus super of up to 17%. The total FTE package will be in the range of $122,358.21–$145,299.95.

The greater benefits of joining the UQ community are broad: from being part of a Group of Eight university, to recognition of prior service with other Australian universities, up to 26 weeks of paid parental leave, 17.5% annual leave loading, flexible working arrangements including hybrid on site/WFH options and flexible start/finish times, and genuine career progression opportunities via the academic promotions process.

Appointment Booklet

Please go to our careers page to view the Appointment Booklet.

About UQ

As part of the UQ community, you’ll have the opportunity to work alongside the brightest minds, who have joined us from all over the world, and within an environment where interdisciplinary collaborations are encouraged.

As part of our commitment to research excellence, we are proud to provide our staff with access to world-class facilities and equipment, and grant writing support.

At the core of our teaching remains our students, and their experience with us sets a foundation for success far beyond graduation. Not only do we have one of the largest PhD enrolments in Australia, but we have also made a commitment to making education opportunities available for all Queenslanders, regardless of personal, financial, or geographical barriers.

About You

UQ is committed to a fair, equitable and inclusive selection process, which recognises that some applicants may face additional barriers and challenges which have impacted and/ or continue to impact their career trajectory. Candidates who may not meet all the selection criteria are strongly encouraged to apply for and demonstrate their potential in the role, even if certain selection criteria can’t be met. Candidates may also wish to proactively outline any barriers or challenges which have impacted their career. The selection panel will consider both your potential and any performance relative to opportunity when assessing your suitability for this role.

Applicants should possess a PhD or be near completion (e.g., thesis submitted) in a relevant field such as mathematics, statistics, mathematical data science, or physics. Additionally, you will demonstrate:

Level A (Associate Lecturer):
• An emerging profile of contributions towards a range of teaching responsibilities, including assisting with designing effective learning materials and assessment tasks, using effective teaching and learning approaches, coordinating courses, and participating in a range of student experiences.
• A developing profile in research in the discipline area, evidence for which can include: a track record of publications in reputed refereed journals and conference presentations; a contribution to the transfer of knowledge, technology, and practices to research end users; and/or the development of partnerships with research end users or external collaborators.
• A plan for a research program that complements and supplements the research of staff in the School and/or the broader university, including details of possible collaborations.
• A growing record of or the potential for effective contributions to the supervision of Honours and Higher Degree by Research students, evidence for which can include: assisting with the supervisory role contributing to successful completion of Honours or HDR students or vacation scholars; development of supervisee capabilities and skills; demonstrating the responsible conduct of research; and/or facilitating engagement opportunities for supervisees.
• Some experience in meaningful internal service roles and/or contributions towards external activities.

Level B (Lecturer):
• A growing profile of contributions towards a range of teaching responsibilities, including designing effective learning materials and assessment tasks, using effective teaching and learning approaches, coordinating courses and participating in a range of student experiences.
• Evidence of participation in education collaborations and professional learning in teaching.
• A developing national profile in research in the discipline area, evidence for which can include: a track record of publications in reputed refereed journals and conference presentations; a contribution to the transfer of knowledge, technology and practices to research end users; and the development of partnerships with research end users or external collaborators.
• Evidence of contributing to and sometimes leading applications for external research funding.
• A growing record of effective supervision of Honours and Higher Degree by Research students, evidence for which can include: supervisory role contributing to successful completion of Honours or RHD students; development of supervisee capabilities and skills; demonstrating the responsible conduct of research; and facilitating engagement opportunities for supervisees.
• Evidence of effective performance in internal service roles in conjunction with active contributions to external activities.

Additional criteria

The University of Queensland considers that the filling of this position constitutes an equal opportunity measure under s105 of the Anti-Discrimination Act 1991(Qld) and under section 8(1) of the Racial Discrimination Act 1975 (Cth).
The position is therefore only open to Australian Aboriginal and/or Torres Strait Islander people.
The successful candidate will be required to provide evidence to confirm that they are an Aboriginal and/or Torres Strait Islander person.

In addition, the following mandatory requirements apply:
Work Rights: You must have unrestricted work rights in Australia for the duration of this appointment to apply. Visa sponsorship is not available for this appointment.

Questions?

For more information about this opportunity, please contact Professor Joseph Grotowski, Head of School – Mathematics and Physics via j.grotowski@uq.edu.au

For application queries, please contact recruitment@uq.edu.au stating the job reference number in the subject line.

Want to Apply?

All applicants must upload the following documents in order for their application to be considered:
• An outline of their research program.
• Resume
• Cover letter addressing (1) the selection criteria, and (2) identifying how their research complements and supplements the research of staff in the School and/or the broader university, including details of possible collaborations.

Please note that you will be asked to add all documents into the one upload box labelled ‘resume’, which is step one of the application form.

About the Selection Process

Please note that seminars, mock lectures, and interviews have been scheduled for 18 August 2023.

As part of the Selection Process, applicants shortlisted for interview will be invited to make a short presentation (5 minutes) to the selection panel about their teaching and research experience to date at the start of their interview.

The University of Queensland is committed to ensuring all candidates are provided with the opportunity to attend the panel interviews, however, for those candidates who are unable to attend in person, video interview options will be available.

To satisfy pre-requisite questions and ensure your application can be considered in full, all candidates must apply via the UQ Careers portal by the job closing deadline or will not be accepted.

Other Information

At UQ we know that our greatest strengths come from our diverse mix of colleagues, this is reflected in our ongoing commitment to creating an environment focused on equity, diversity and inclusion. We ensure that we are always attracting, retaining and promoting colleagues who are representative of the diversity in our broader community, whether that be gender identity, LGBTQIA+, cultural and/or linguistic, Aboriginal and/or Torres Strait Islander peoples, or people with a disability. Accessibility requirements and/or adjustments can be directed to recruitment@uq.edu.au

If you are a current employee (including casual staff and HDR scholars), or hold an unpaid or affiliate appointment with the University, please login to your staff Workday account and visit the internal careers board to apply for this opportunity. Please do NOT apply via the external job board.

Links for application/more information

For candidates to apply, they will need to please visit https://uq.wd3.myworkdayjobs.com/uqcareers/job/St-Lucia-Campus/Associate-Lecturer-Lecturer–Level-A-or-B–Mathematics-or-Physics–Identified-Position-_R-27253-2.

Lecturer in Mathematics @Sydney

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Closing date: 17 August 2023; 11:59pm
Campus: School of Mathematics and Statistics at the Camperdown Campus, The University of Sydney
Remuneration: Base Salary Level B, $113K – $134K + 17% superannuation
Status: Full time, 3 years, fixed term.
Reference: 0107501-1

• Full time, 3 Years Fixed Term. Located on the Camperdown Campus at the School of Mathematics and Statistics
• Opportunity to join a vibrant and collegial community of world-class mathematicians and statisticians
• Base Salary, Level B $113K – $134K p.a. + 17% superannuation

About the opportunity

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. The University also hosts the Sydney Mathematical Research Institute (SMRI), which attracts leading mathematical scientists from all over the world to do research with Australian collaborators. 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.

About you

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Lecturer/Senior Lecturer who has:

• a PhD in Mathematics
• evidence of independent research ability
• demonstrated evidence of independent research ability and potential in an area of Mathematics
• published research, as a sole author or in collaboration, in refereed journals
• evidence of ability, versatility and commitment to excellence in undergraduate teaching
• ability to supervise students at undergraduate and postgraduate levels
• evidence of administration and course coordination within a university environment and the ability to apply for competitive research funding would be highly desirable.

The position is full-time fixed-term for three years, subject to completion of a satisfactory probation and confirmation period for new appointees.

To apply for this role, please submit the below three documents in addition to your CV, in support of your application:

  1. cover letter outlining your suitability for this position
  2. research statement, with a focus on where you see your research in 3 years
  3. teaching statement, with a focus on approaches you utilize for effective teaching

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

For more information and to apply: https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Darlington-Campus/Lecturer-in-Mathematics_0107501-1

© The University of Sydney
The University reserves the right not to proceed with any appointment.

Postdoc in Mathematical Biology at Univ. Sydney

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Location: School of Mathematics and Statistics, The University of Sydney
Employment Type: Full time 2 year fixed term
Duration: 2 years fixed term appointment
Remuneration: $97,043–$100,717 p.a. + 17% superannuation (Level A)
Closing Date: 11.59pm; 13 August 2023

About the opportunity

We are seeking to appoint a Postdoctoral Research Associate in Mathematical Biology (with a focus on modelling the immune system) to conduct innovative research in mathematical and computational modelling of immune system dynamics. The position will be under the supervision of Prof Peter Kim (University of Sydney).

Some of your responsibilities will be to:

• work under the supervision of Prof Peter Kim in collaboration with Prof Federico Frascoli (Swinburne University of Technology), Dr Robyn Araujo (Queensland University of Technology), and Prof Peter Lee (City of Hope and Beckman Research Institute, Duarte, USA)
• develop mathematical and computational models of immune dynamics
• write scholarly papers for publication in academic journals
• present research at seminars, conferences, and workshops
• teach undergraduate courses (approximately 26 lecture hours and 24 tutorial hours per year)

This position has been made possible by the awarding of an Australian Research Council Discovery Project to chief investigators Prof Peter Kim (University of Sydney), Prof Federico Frascoli (Swinburne University of Technology), Dr Robyn Araujo (Queensland University of Technology), and partner investigator Prof Peter Lee (City of Hope and Beckman Research Institute, Duarte, USA).

To learn more about the School of Mathematics and Statistics click here.

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Pre-employment checks

Your employment is conditional upon the completion of all roles required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

Learn more about this position and apply: https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Darlington-Campus/Research-Associate-in-Mathematical-Biology–with-a-focus-on-Modelling-the-Immune-System-_0105303-1.

Postdoctoral Research Fellow in Statistical Mechanics

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Location: School of Mathematics and Statistics, The University of Melbourne
Level: A/B
Duration: 2 years
Closing date: 5 August 2023

This is an exciting opportunity to work on the Australian Research Council funded project “Transformative simulation techniques for complex networks” with a team of esteemed researchers led by Professor Aleks Owczarek and Dr Nicholas Beaton. The project aims to expand the simulation of single-lattice polymer models in statistical mechanics to a range of complex topologies and complicated interacting environments using next generation simulation algorithms on modern computational clusters.

The project provides a unique platform to collaborate with leading researchers around the world based at the Queen Mary University of London, University of British Columbia and Swinburne University of Technology.

You will significantly contribute towards the research effort of the team and to develop your research expertise with an increasing degree of autonomy under the guidance (at Level A) and in collaboration (at Level B) of Senior Academic staff conduct internationally competitive research, resulting in publications in high impact journals. In particular you are expected to progress the research agenda described in the ARC DP230100674 proposal as developed by the CIs, and contribute to teaching, training, scientific mentoring and supervision of students

For more information and to apply, see https://jobs.unimelb.edu.au/caw/en/job/913201/postdoctoral-research-fellow-in-statistical-mechanics.

FairML Postdoc opportunity at CSIRO

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Location: CSIRO’s Data61
Closing Date: 31 August 2023
Duration: 3 years

Machine Learning (ML) is increasingly used to inform high-stake, human-centric decisions including credit scoring and sentencing in the judiciary system. But ML algorithms are well-known to exhibit biases disadvantaging people from certain ethnicities and genders. Fairness research has contributed more equitable algorithms and has increased our understanding on different bias sources. However, an understanding of how these bias sources combine to forge the overall bias is still lacking. This project aims to disentangle ML-bias into algorithmic and data bias focussing on intersectional subgroups. The techniques developed can then be used to analyse biases in threatened species management and human–machine collaboration.

For more information and to apply, click here.

Learning Success Advisor @Sydney

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Location: Student Support Services, The University of Sydney, Camperdown Campus
Employment Type: Full time
Duration: continuing
Remuneration: Base Salary $100,032–$108,979 + 17% superannuation
Closing Date: 11.59pm; 17 July 2023

• Exciting opportunity to facilitate and deliver mathematics and statistics learning support for students at the University

About the opportunity

As a Learning Success Adviser (Mathematics), you will act as an integral member of a team of specialist professional staff focusing on student facing support. You will be working in a fast-paced environment where you will help develop, deliver, and evaluate mathematics and statistics learning support initiatives for all students at the University. You will play a pivotal role in contributing to the University’s strategic initiatives for the provision of learning support.

As a subject matter specialist, you will collaborate in the development and implementation of learning support initiatives, including student-centred learning design, personalised and adaptive support offerings, through a variety of delivery modes such as face to face, online, blended, hybrid and peer-facilitated.

Your key responsibilities will be to:

• help students to develop their confidence in mathematics and statistical skills, enhancing their experience and supporting fuller participation and success in relevant units of study.
• deliver learning support & training activities to students, peer-facilitators, & staff for up to 20 hours a week
• work within a dynamic team, reporting to the Learning Hub Lead
• deliver learning support & training activities to students, peer-facilitators, & staff for up to 20 hours a week
• work collaboratively with the Learning Hub Lead, and collaboratively with other Learning Success Advisors, the Ed Services team, and colleagues across CET + Learning Hub • provide guidance and support to relevant stakeholders in relevant faculties, library, Educational Innovation, Student Life, and the wider Education Portfolio
• engage in and contribute to continuing professional development within the CET + Learning Hub unit and externally to ensure implementation of best practice in mathematics and numeracy learning support and maintain current knowledge of the high school and relevant University-level curricula
• contribute to and engage actively with the mathematics and statistics learning community beyond the University to further the reputation of the University in the field.

About you

• a strong background and experience in tertiary mathematics and/or statistics (post graduate qualifications and/or relevant work experience in a related field are highly desirable)
• experience in teaching and learning in a tertiary environment, with an emphasis on settings relevant to mathematics and statistics support
• experience in developing and facilitating high-quality, innovative programs to support mathematics and statistics learning in a higher education environment
• experience using learning analytics to inform learning design, support student progress and monitor student outcomes
• experience using innovative educational technology platforms to facilitate mathematics and statistics support to diverse cohorts of students
• theoretical and practical understanding of effective educational practice in the higher education space, including the use of educational technologies.

This will be a continuing appointment. The successful candidate will be offered a competitive remuneration package commensurate with the responsibilities of the position and the candidate’s relevant experience and qualifications.

Other

To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus.

Sponsorship / work rights for Australia

Please note: Visa sponsorship is not available for this position. For a continuing position, you must be an Australian or New Zealand citizen or an Australian Permanent Resident.
Australian Temporary Residents currently employed at the University of Sydney may be considered for a fixed term contract for the length of their visa, depending on the requirements of the hiring area and the position.

Pre-employment checks

Your employment is conditional upon the completion of all roles required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

This position is designated as involving child-related work. To undertake or remain in this position, you are required to apply for and obtain a Working with Children Check clearance in accordance with the Child Protection (Working with Children) Act 2012.

EEO statement

At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community which reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.

How to apply

Apply via this link: https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Darlington-Campus/Learning-Success-Advisor–Mathematics-_0106000-2

For a confidential discussion about the role, or if you require reasonable adjustment, or any documents in alternate formats, please contact Felicity Appleby, Recruitment Operations by email to recruitment.admin@sydney.edu.au.

© The University of Sydney

The University reserves the right not to proceed with any appointment.

Research Fellow in Theoretical and Computational Fluid Dynamics @Monash

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Location: School of Mathematics, Monash University
Employment Type: Full-time
Duration: 2-year fixed-term appointment
Remuneration: $78,120–$106,022 p.a. Level A (plus 17% employer superannuation)
Closing Date: 16 July 2023, 11:55 pm AEDT
Job No. 652902

The School of Mathematics at Monash University invites applicants for the position of Research Fellow in Theoretical and Computational Fluid Dynamics. The successful candidate will work on an ARC Discovery Project led by Dr Kengo Deguchi, involving mathematical analysis of multiscale coherent structures in various shear flows and engage in developing related computational tools to be enabled by the international interdisciplinary collaboration between the Mathematics and Engineering communities in Australia and Japan.

Applicants must have a PhD in Mathematics, Physics, Engineering or a related field. Applicants must have a strong background in the theoretical analyses of Navier–Stokes equations (e.g., linear and nonlinear stability analyses, asymptotic analysis, dynamical systems theory) and expertise in the numerical calculations related to the analyses.

Applications must be made via: https://careers.pageuppeople.com/513/cw/en/job/652902/research-fellow-in-theoretical-and-computational-fluid-dynamics.

Lecturer in Mathematics @Notre Dame

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Location: The University of Notre Dame Australia; Sydney campus, School of Arts & Sciences
Employment Type: Level B, 0.8 FTE
Duration: Continuing
Closing Date: 2 July 2023

The University of Notre Dame Australia is a private Catholic University with over 1,000 permanent staff providing an exceptional educational experience to over 12,000 students across our Fremantle, Broome, and Sydney campuses, as well as clinical schools in Victoria and New South Wales.

The purpose of this position is to conduct research and deliver courses, including online courses, in mathematics. A level B Academic Staff Member is expected to make contributions to the teaching effort of the institution and to carry out activities to maintain and develop their scholarly, research and/or professional activities.

Aboriginal and Torres Strait Islander people are encouraged to apply.

For more information and to apply, please visit this page.