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.

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.

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.