Author: Mikael Vejdemo-Johansson

We are excited to announce that the 13th edition of the conference Algebraic Topology: Methods, Computation and Science (ATMCS13) will be held at KTH in Stockholm from 28 June to 2 July 2027.

The conference will feature talks by invited speakers, as well as contributed talks and poster presentations, selected by a scientific committee.

The registration and abstract submission will open at the end of November. The conference website will be updated regularly as further information becomes available, including abstract submission and registration deadlines.

The line-up of plenary speakers is as follows:

•   Håvard Bjerkevik
•   Omer Bobrowski
•   Thomas Brüstle
•   Daniela Egas Santander
•   Yasuaki Hiraoka
•   Christian Hirsch
•   Ingrid Hotz
•   Anthea Monod
•   Bastian Rieck
•   Erin Chambers (TBC)

The scientific committee consists of:

•   Henry Adams (co-chair)
•   María-José Jimenez (co-chair)
•   Tamal Dey
•   Ellen Gasparovic
•   Lida Kanari
•   Claudia Landi
•   Elizabeth Munch
•   Nina Otter
•   Siddharth Pritam
•   Rubén Sánchez-García
•   Kate Turner
•   Kelin Xia

We look forward to seeing you in Stockholm!

The organisers (Wojciech Chachólski, Anna Schenfisch, Martina Scolamiero, Francesca Tombari)

Morten Brun writes:
We are advertising a PhD Research Fellow position in Topological Data Analysis at the University of Bergen, Norway.

I would particularly like to bring the position to the attention of students with a background in algebraic topology, including students who have not previously worked in topological data analysis or thought of themselves as applied mathematicians.

Topological data analysis uses ideas from algebraic topology to study data and, at the same time, raises new mathematical questions about filtrations, persistence, stability, and computable topological invariants. A student with a strong interest in algebraic topology who would like to explore this interface between topology, computation, and data would therefore be very welcome to apply.

Full details, including qualifications, application procedure, and deadline, are available here:

https://www.jobbnorge.no/en/available-jobs/job/308312/phd-research-fellow-in-topological-data-analysis

Tim Ophelders writes:
TLDR: PhD position in Computational Geometry and Computational Topology at TU Eindhoven (TU/e)

Apply here by October 2: https://www.tue.nl/en/working-at-tue/vacancy-overview/phd-in-computational-geometry-and-computational-topology

The Project

Computational geometry and computational topology are areas of research focused on the design and analysis of algorithms for spatial data. These algorithms typically leverage geometric and topological structure present in the data to obtain efficient solutions. This project focuses on computing similarities between networks in a spatial context, such as networks embedded in the Euclidean plane, or on a terrain. We intend to develop topology- and geometry-aware graph edit distances, drawing inspiration from well-studied variants of the Fréchet distance between curves. This project has a vacancy for one PhD student.

Tasks

As a PhD student working on the project, your main task will be to perform research, in close collaboration with your advisory team and others involved in the project. The advisory team consists of dr. Tim Ophelders and prof. dr. Bettina Speckmann. One PhD student is already working on the project. Your tasks as a PhD student also include participating in international conferences and workshops to present your results. Besides working on your research project, you will also assist in some algorithms-related courses, as a teaching assistant (TA).

You will be working in the TU/e Algorithms cluster (algo.win.tue.nl), one of the largest research groups world-wide that focuses on algorithms research. The cluster is known for its research in computational geometry and topology, algorithms for spatiotemporal data, and algorithmic visualization, as well as graph and FPT algorithms. The cluster provides a lively and international environment for your research.

As a PhD student, you do need not speak Dutch: it is easy to get by with English, not only at the university (where all courses are taught in English) but also in everyday life.

Requirements

 – A master’s degree (or an equivalent university degree) in computer science or mathematics, with a strong background in algorithms.

 – A passion for research in computational geometry and computational topology

 – An interest in teaching algorithms-related courses

 – Fluency in spoken and written English (C1 level)

Employment Benefits

 – Full-time employment for four years, with an intermediate assessment after nine months. You will spend a minimum of 10% of your four-year employment on teaching tasks, with a maximum of 15% per year of your employment.

 – Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. € 3,059 – max. € 3,881), with a year-end bonus of 8.3% and annual vacation pay of 8%.

 – An excellent technical infrastructure, on-campus children’s day care and sports facilities.

 – A staff immigration team and a tax compensation scheme for international candidates. 

Applying

All applications should be submitted through the TU/e application website: https://www.tue.nl/en/working-at-tue/vacancy-overview/phd-in-computational-geometry-and-computational-topology

For full consideration, apply by October 2, 2026.

Questions

If you have questions about the position or project, please contact dr. Tim Ophelders ([email protected])

It is with deep sadness that I share the news that Mariel Vázquez has passed on. Sociedad Matemática Mexicana announced the loss on Facebook. Our condolences go out to her family, friends and colleagues, and I am happy for the conferences I have been able to share with her.

We are pleased to announce that registration is now open for the conference:

Mathematical Structure in Data: Topology, Geometry, and Applications,

which will take place at Penn State in State College, Pennsylvania, on September 30–October 1, 2026.

This conference will bring together researchers developing mathematical methods for identifying and analyzing the geometric and topological structure in data, with topics including manifold learning, topological data analysis, geometric and spectral methods, and related approaches.

Invited speakers include:

• Lisa Fauci (Tulane University)

• Kevin Flores (North Carolina State University)

• Marc Gilles (Princeton University)

• Heather Harrington (MPI-CBG)

• Liz Munch (Michigan State University)

• Tatyana Sharpee (Salk Institute)

• Suzanne Sindi (University of California, Irvine)

• Guowei Wei (University of Georgia)

Participants interested in attending or presenting a poster are encouraged to register through the conference website:

https://sites.google.com/view/msdtga-2026/home

We would be delighted to welcome you to Penn State for this meeting.

Best,

Sara Kališnik

Wenrui Hao

John Harlim

Vladimir Itskov

As I arrive in Washington DC for the Joint Mathematics Meetings, starting tomorrow, it’s time to write another short guide to what I’ve spotted in the program this year. As several earlier years, a LOT of the relevant sessions have been scheduled in parallel, especially on the last day of the conference.

If you are interested in TDA and adjacent topics, you may be interested in:

• AMS Special Session on TDA for Non-linear dynamics
  Sunday 2026-01-04, 08:00 – 12:00, 13:00 – 17:00 in Room 209C
  • Justin Curry: Stratification Theory for Reinforcement Learning
  • Andrei Zagvozdkin et al: Topological Deep Learning and Physics-informed Neural Networks for PDEs on Riemannian Manifolds
  • Michael Robinson: The appearance of stratified spaces in synthetic aperture sonar collections
  • Sara Tymochko et al: Evaluating Resource Coverage using TDA
  • Vitaliy Kurlin: Data Science reveals the stochastic nature of proteins and AlphaFold predictions
  • Maxwell Chumley et al: Dynamical System Parameter Path Optimization using Persistent Homology
  • Sunia Tanweer et al: Phenomenological Bifurcations in Compartmental Stochastic SIS and SIR Models for Epidemiology
  • Himanshu Yadav: Topological Structure of the Cyclonic-Anticyclonic Interactions
  • Soheyl Anbouhi: Improving Topological Detection of Weather Regimes in Climate Dynamical Systems
  • Jacob Bali Sriraman: Topological Time Series Analysis of the Polar Vortex
  • Tung Lam: Delaunay Filtrations for Time-Varying Data
  • James George Moukheiber et al: TDA for Geographical Information Science: Slum Detection and Satellite Imagery
• Steve Huntsman: Motivating coherence-driven inference via sheaves
  Sunday 2026-01-04, 08:00 – 08:30 in Room 102A in the AMS Special Session on Mathematics for AI Robustness, Explainability, and Safety
• Radmila Sazdanovic: The Art of Knot Data
  Sunday 2026-01-04, 11:00 – 11:30 in Room 143A in the SIGMAA Special Session on Mathematics and the Arts
• Radmila Sazdanovic: TDA of Classical and Quantum Invariants
  Sunday 2026-01-04, 13:30 – 14:00 in Room 140B in the AMS Special Session on Knots, Links, Geometry, and related 3-manifolds

• Paul Schrader: Dilating Mission Relevant Impacts of Autonomous Data Driven Topologically-Informed Analytics and Fusion
  Monday 2026-01-05, 10:00 – 11:00 in Room 204A in the AMS Special Session on Data Fusion: Methods, Modeling, and Emerging Applications
• Abigail Hickok: Persistent Homology for Resource Coverage: A Case Study of Access to Polling Sites
  Monday 2026-01-05, 13:30 – 14:00 in Room 141 in the AMS Special Session on The Mathematics of Elections and Redistricting

• SIAM Minisymposium on Geometric and Topological Data Analysis with Applications
  Tuesday 2026-01-06, 08:30 – 12:00 in Room 152B
  Wednesday 2026-01-07, 13:00 – 17:00 in Room 152A
  • Drumea Bianca et al: Investigating the Structure of LK-99 using TDA: A Challenge to Superconductivity Claims
  • Benjamin Daniel Jones et al: Efficient Computation of Persistent Topological Laplacians
  • Benjamin Schweinhart: Representations of Micrograph Geometry for Machine Learning
  • Melinda Kleczynski et al: TDA and Multidimensional Scaling for Mass Spectral Libraries
  • Tyrus Berry: Persistent and Coarse Geometry for Comparing Point Clouds
  • Vitaliy Kurlin: Extending persistence to sttronger and faster invariatns of clouds under isometry
  • Graham Johnson et al: Topological Deep Learning for Energy Systems: from TDA Features to Higher-Order Relations
  • Jeanie Schreiber: Topological Shape and Data Analysis for Materials EBSD Imaging
  • Jacob Dylan Rezac et al: Inversion-free Segmentation for Linear Inverse Problems with Shape Priors
  • James Derek Tucker: Elastic Functional Bayesian Model Calibration of Curves in R^N
  • Sebastian Kurtek: Assessment of Spatial Dependence in Shapes of Planar Curves
  • Nicholas Charon et al: SVarM: regression and classification in the space of varifolds

• AMS Special Session on Open Problems in Geometric Data Science
  Wednesday 2026-01-07, 08:00 – 12:00, 13:00 – 17:00 in Room 209C
  • Simon Billinge: Continuous representations of crystals and why that is important for materials and mankind
  • Vitaliy Kurlin: The fundamental questions of Geometric Data Science
  • Harm Derksen: Low distortion Euclidean embeddings for datawith group symmetries
  • Gregor Kemper: Distance geometry, algebra and drones
  • Kathlen Kohn: Viewing Graph Solvability in Computer Vision through the lens of Rigidity Theory and Algebraic Geometry
  • Frank Sottile: Algebraic geometry of periodic graphs operators
  • Erica Flapan: Topological complexity in protein structures
  • Madeleine Clore et al: Mechanistic interpretation of spurious AlphaFold2 predictions
  • Maria Kourkina Cameron: Learning coarse-grained models for molecules and atomic clusters
  • Peter Bubenik et al: Topological Featuer Selection for Time Series Data
  • Sushovan Majhi et al: Vietoris-Rips Shadow for Euclidean Graph Reconstruction
  • Mateo Diaz et al: Any-dimensional equivariant learning
  • Zawad Chowdhury et al: Graphical Designs and Combinatorial Structures

• AMS Special Session on Topological and Geometric Shape Reconstruction
  Wednesday 2026-01-07, 09:00 – 12:00, 13:00 – 16:30 in Room 151B
  • Kevin Knudson et al: Discrete Morse Theory for open complexes
  • Ziga Virk: Contractibility of the Rips complexes of Integer lattices via local domination
  • Peter Bubenik et al: Cycle representatives for persistent homology – localization, statistics and visualization
  • Facundo Memoli et al: The G-Gromov-Hausdorff Distance and Equivariant Topology
  • Henry Adams: Bridging applied and quantitative topology
  • Michael Robinson: Using multi-jet transversality to reconstruct LLM token subspaces
  • Conglong Xu: Stochastic Gradient Descents on Riemannian Manifolds with Applications on Machine Learning Problems
  • Luiz Hartmann et al: Analyzing Covariance on Graph-Structured Data via Generalized PCA
  • Rafal Komendarczyk et al: From Samples to Graphs: Homeomorphic Geometric Reconstruction with Intrinsic Rips

Andrea Guidolin writes:
I would like to advertise a fully funded 3.5-year PhD position at the University of Southampton to work on an interdisciplinary project titled “Topological simplification of single cell data” under the supervision of Professor Ben MacArthur, Professor Ruben Sanchez-Garcia, and myself. The aim of the project is to use topological data analysis to simplify the complex dynamics of single cell data and identify combinations of genes that oscillate in a coordinated manner. The position is co-funded by the Institute for Life Sciences and the School of Mathematical Sciences at the University of Southampton.

We welcome applications from candidates with a background and/or interest in (applied) algebraic topology or topological data analysis and who are keen to contribute to exciting interdisciplinary research at the interface of Mathematics and Biological Sciences.

To apply for the position, please follow the link below and indicate my name and the project title:

https://www.southampton.ac.uk/study/postgraduate-research/apply
Applications will be reviewed on a rolling basis but we strongly encourage interested candidates to apply before 15 January 2026. The successful candidate must be enrolled on or before 1 January 2027.

For any question, you are welcome to email me at ([email protected]).

The algebraic topology group of the Ecole Polytechnique Fédérale de Lausanne (EPFL) invites applications for one full-time postdoctoral position in algebraic topology, pure or applied.

This two-year position has a starting date of 1 September 2026 and is open to all candidates with a PhD from no earlier than 2022 who have shown promise of research excellence in pure or applied topology.

In addition to research, duties of the future postdoc will include teaching within the framework of the Mathematics Section of the EPFL.

EPFL salaries are highly competitive.  The group has considerable travel money available for postdocs, as well as a generous budget for inviting guests throughout the year.

Applications, including letter of motivation, CV with publication list, and research plan must be submitted by December 15 via the online application form.  Three letters of recommendation should be sent to [email protected] by the same date.

For further information, please feel free to contact either of us.

Best wishes,
Kathryn Hess and Jérôme Scherer

Christian Pascal Hirsch writes:
It is our pleasure to announce the workshop “H2O: Higher-Order pattern-discovery in High-dimensional data ” at Aarhus University, March 30 & 31, 2026. This is a two-day event designed to forge new connections across three distinct fields of modern statistical research: topological data analysis (TDA), time-series analysis (TSA), and high-dimensional statistics (HDS). At the intersection of these fields lies the critical challenge of identifying patterns in complex data structures, particularly in network data. The workshop features presentations by leading experts in the respective disciplines. 

Our primary audience includes both senior and junior researchers working in mathematical statistics and data science.

The invited lecturers are:

• Martin Bladt (University of Copenhagen)
• Axel Bücher (Ruhr-University Bochum)
• Johannes Heiny (Stockholm University)
• Moritz Jirak (University of Vienna)
• Enno Mammen (Heidelberg University)
• Alexei Onatskiy (University of Cambridge)
• Martina Scolamiero (KTH Stockholm)
• Claudia Strauch (Heidelberg University)

We can provide a very small number of accommodation in double rooms for PhD students/postdocs who have no other funding possibilities (separated by gender). Similarly, we can provide reimbursement for train/flight tickets to a very small number of PhD students/postdocs (at most DKK 1500 per person).

Deadline for registration with submitted talk/request for reimbursement: December 12, 2025

Further information can be found at https://www.aarhush2o.live/