We are pleased to announce that next year’s Young Topologists Meeting will take place between 12-16 July 2021 in Stockholm, jointly organized by the KTH Royal Institute of Technology and Stockholm University.
The intention of the conference is to create a setting in which young researchers in topology can meet each other and share their work. The program will consist of short talks given by the participants and three lecture series by invited speakers. This meeting serves as a replacement for the YTM 2020, which had to be cancelled because of the ongoing COVID-19 pandemic. In particular the invited speakers are the same ones that were invited for this year’s edition: Kathryn Hess (EPFL), Thomas Nikolaus (WWU Münster) and Karen Vogtmann (Cornell University and University of Warwick).
Kathryn Hess, Frédéric Chazal and Umberto Lupo are curating an Article Collection published in Frontiers in Artificial Intelligence and entitled “Topology in Real-World Machine Learning and Data Analysis” (webpage). Its core mission is to promote the use of topological ideas and techniques as mainstream tools in data science. We welcome contribution(s) to our Article Collection. Papers can be original research, reviews, or perspectives, among other article types. Deadlines are as follows:
17 August 2020 – Abstracts (soft deadline);
14 December 2020 – Manuscripts.
Upon publications, papers will be free to read for everyone. There are processing charges associated to publishing with Frontiers in AI, but waivers can be applied for if your institution or grant does not cover Open Access fees. Please get in touch if you would like to learn more about scope, deadlines, and publishing fees. Alternatively, you can sign up for participation directly from the Collection’s webpage. Best wishes,Umberto, Kathryn, Frédéric
Dr. Veronica Ciocanel and Dr. Wasiur KhudaBuksh are organising a virtual mini-symposium on “Probabilistic and Topological Methods for Biological Data” as part of the SIAM conference on Mathematics of Data Science 2020. More information below.
Time: June 11, 2020 1-3pm EST (topology session) and 3-5pm EST (probability session)
Registration: Registration is free (and would take less than 30 seconds), but limited to 300 people. Link here:
Speakers in the topology session: 1. Francis Motta, Florida Atlantic University 2. Marilyn Vazquez, the Ohio State University 3. Veronica Ciocanel, the Ohio State University 4. Manuchehr Aminian, Colorado State University
Speakers in the probability session: 1. Wasiur KhudaBukhsh, the Ohio State University 2. Arindam Fadikar, Argonne National Lab 3. Pragya Sur, Harvard University 4. Yuekai Sun, University of Michigan
The talks will cover many different application areas ranging from microscopic cell biology to macroscopic epidemiology using tools from topology and probability theory.
The Dioscuri Center is a new research center for Topological Data Analysis, to start in July 2020 and led by Dr Pawel Dlotko.
The Dioscuri Center is seeking a postdoctoral researcher for a fixed-term 24-month position to work on developing mathematically rigorous geometry and topology based shape descriptors to solve important applied problems.
We invite applications for a Postdoctoral Research Associate in Topological Data Analysis to work with Professors Heather Harrington and Ulrike Tillmann here at the Mathematical Institute, University of Oxford. The position is fixed-term for 30 months (2.5 years), and the successful candidate will become a member of the Centre for Topological Data Analysis at Oxford.
The postholder will be responsible for conducting research in applied topology, including topological data analysis, as well as techniques within computational topology aimed at bridging levels of organisation within molecular biology. You will be expected to contribute ideas for new research projects, write up the results of your research for publication, and provide guidance to junior members of the research group including project students, PhD students, and/or project volunteers.
Applicants will be expected to have, or be close to completing, a PhD in computational mathematics, topology or applied algebra. You will possess sufficient specialist knowledge to work within the research interests of the Centre for Topological Data Analysis, alongside the ability to manage your own research and administrative activities. Previous experience of computational mathematics and/or computer programming is desirable.
Applicants will be selected for interview based on their ability to satisfy the selection criteria as outlined in the job description document below. You will be required to upload a letter setting out how you meet the selection criteria, a curriculum vitae including full list of publications, a statement of research interests and the contact details of two referees as part of your online application (NOTE: Applicants are responsible for contacting their referees and making sure that their letters are received by the closing date).
Only applications received before 12.00 noon on Wednesday 17 June 2020 can be considered. Interviews are anticipated to take place week commencing Monday 29 June 2020.
The Laboratory for Topology and Neuroscience (EPFL) invites applications for two postdoctoral positions in topological data analysis and machine learning affiliated with the project “Topological suite for deep learning: enhanced model reliability, stability and performance”, financed by Innosuisse (Swiss Innovation Agency) and carried out in collaboration with the Reconfigurable and Embedded Digital Systems lab (HEIG-VD) and L2F, an EPFL start-up founded in 2017 to develop innovative machine learning pipelines integrating notions from fundamental mathematics, in particular algebraic topology.
The aim of this project is to discover and develop new topological tools to unbox artificial intelligence and to enhance the robustness, performance, and reliability of deep learning models.
The postdocs selected will be members of the Laboratory for Topology and Neuroscience and collaborate with L2F and REDS.
Candidates should hold a PhD from no earlier than 2016 in mathematics, physics, or computer science, have some familiarity with topological data analysis, and be proficient Python coders. Please send your cover letter, CV, and publication list to Kathryn Hess at email@example.com, to whom you should arrange for three letters of reference to be sent as well.
Starting date: 1 October 2020 or as soon as possible thereafter Duration: 24 months Application deadline: 30 May 2020
A postdoc position is available at the School of Physics and Mathematics, Nanyang Technological University (NTU) in Singapore.
The annual salary will be about 55000-70000 SGD/year (dependent on previous qualifications and experience) with an additional performance bonus of up to 3 months (Income tax rate is ~4%). The position will start at about Aug 2020. It will be 2 years and can be extended to 3 years.
The research areas of the candidate should be on applied topology, computational topology, computational geometry, and machine learning. The ideal applicant should have good training on computation, algorithm design and modeling. Previous experience on biomolecular modeling and biomolecular data analysis is preferred but not necessary.
For those interested, please send CV, research statement, and contact information for three references to Prof. Kelin Xia at firstname.lastname@example.org.