蒙纳士大学（Monash University），又译莫纳什大学，坐落于澳大利亚文化、艺术与工业中心墨尔本，是一所公立综合类研究型大学，同时是澳大利亚八校联盟、环太平洋大学联盟、国际大学气候联盟与英联邦大学协会成员 。大学于1958年由澳大利亚联邦政府通过议会法案建立，为纪念杰出的军事指挥官、公共行政官员和土木工程师约翰·莫纳什爵士（Sir John Monash），大学以其姓氏命名，官方中文名称为蒙纳士大学。
Research Fellow - Scientific Computing and Numerical Analysis (polytopal methods)
Job No.: 647147
Location: Clayton campus
Employment Type: Full-time
Duration: 2-year fixed-term appointment
Remuneration: $75,115 - $101,944 pa Level A (plus 17% employer superannuation)
Amplify your impact at a world top 50 University
Join our inclusive, collaborative community
Be surrounded by extraordinary ideas - and the people who discover them
At Monash, work feels different. There's a sense of belonging, from contributing to something groundbreaking – a place where great things happen. We make tangible contributions because our purpose is clear; to deliver positive economic, social and environmental impact in resolving the global challenges of our age.
At the core of achieving this purpose is the diversity of our staff. We welcome and value everyone's contributions, lived experience and expertise. When you come to work, you can be yourself, be a change-maker and develop your career in exciting ways. This is why we champion an inclusive and respectful workplace culture where everyone is supported to succeed.
Together with our commitment to academic freedom, you will have access to quality research facilities, infrastructure, world class teaching spaces, and international collaboration opportunities.
The School of Mathematics at Monash University invites applicants for the position of Research Fellow to work on a project in Scientific Computing and Numerical Analysis.
The successful candidate will work under the guidance of Professors Jérôme Droniou and Santiago Badia on the ARC-funded project “Interface-aware numerical methods for stochastic inverse problems”. The role includes the design and analysis of hybrid high-order schemes for partial differential equations with interfaces. The methods will rely on polytopal meshes obtained from adaptive tree-based unfitted meshes. The research also includes optimal and scalable parallel multilevel solvers for the discrete systems arising from hybrid approximations. The role will possibly include the combination of these tools with multilevel Monte Carlo methods and its application to stochastic inverse problems in subsurface modelling.
Applicants must have a PhD in Mathematics or a related field, with a strong background in numerical methods for partial differential equations.
Diversity is one of our greatest strengths at Monash. We encourage applications from First Nations people, culturally and linguistically diverse people, people with disabilities, neurodiverse people, and people of all genders, sexualities, and age groups.
Monash avidly supports flexible and hybrid working arrangements. We have a range of policies in place enabling staff to combine work and personal commitments more easily.
This role is a full-time position; however, flexible working arrangements may be negotiated.
At Monash University, we are committed to being a Child Safe organisation. This position at the University will require the incumbent to hold a valid Working with Children Check.
Your application must address the selection criteria. Please refer to "How to apply for Monash Jobs".