Postdoctoral Researcher
1 week ago
About the Role
We are seeking a highly skilled Postdoctoral Research Assistant to join our team at Queen Mary University of London. The successful candidate will work closely with Dr. Omer Bobrowski on the project "Universality in Topological Data Analysis", funded by the EPSRC.
Key Responsibilities
- Conduct research in probability theory and applied topology, focusing on phase transitions related to the topology of high-dimensional structures.
- Develop and implement machine learning algorithms to analyze and visualize topological data.
- Collaborate with the research team to publish high-quality research papers in top-tier journals.
- Participate in the development of new research projects and proposals.
About the School
The School of Mathematical Sciences at Queen Mary University of London is a world-renowned institution with a strong research presence across the spectrum of mathematical sciences. Our faculty comprises 85 academic staff, 16 research assistants, and 14 members of professional services staff, with a student population of around 80 PhD students, 1,000 undergraduates, and 100 master's students.
Benefits
- Access to a generous pension scheme.
- 30 days' annual leave.
- A season ticket loan scheme.
- Comprehensive range of personal and professional development opportunities.
- Flexible working arrangements.
- Campus facilities, including an on-site nursery at the Mile End campus.
Requirements
- PhD degree in mathematics or equivalent level of professional qualifications and experience.
- Research experience in probability theory and/or applied topology.
- Experience in writing high-quality research papers.
- Expertise in machine learning, applied topology, and/or probability theory.
Equality, Diversity and Inclusion
Queen Mary University of London is committed to the equality of opportunities and to advancing women's careers. We are a registered supporter of the LMS Good Practice scheme and hold a departmental Bronze Athena SWAN Award. We strongly encourage applications from female applicants.
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