Applied Topology

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

 Call for Contributions: TopoInVis Connect 2026 – Topology Meets Artificial Intelligence

TopoInVis Connect: Topology Meets Artificial Intelligence is an inclusive forum dedicated to the latest advances in topological methods spanning theory, algorithms, systems, and applications across visualization and artificial intelligence.

The 2026 edition introduces a new bridge-building format for TopoInVis, explicitly fostering connections between the VIS community and researchers in AI, machine learning, computational geometry, and related domains where topology plays a central role.

We invite full-paper submissions exploring the intersection of topology, visualization, and AI, including both foundational research and applied contributions.

Accepted papers will be presented at IEEE VIS 2026 in Boston, MA, and published as regular workshop proceedings.

 Important Dates

* Abstract Deadline: June 15, 2026

* Submission Deadline: June 22, 2026

More details: [link]

On behalf of the Organization Committee

Federico Iuricich, Yue Zhang, Mathieu Carrière, Tobias Günther, Raghavendra Sridharamurthy, Wiebke Köpp

Dear colleagues, 

This is to announce the first meeting of a new series of events at CTA^2 – Center for Topology, Algebra, and their Applications, titled

Workshop on Spatial Structures

21-25 September 2026

at Vrije Universiteit Amsterdam, Netherlands. 

More information and registration: 

https://sites.google.com/vu.nl/cta2spatialstructures

Registration deadline: 1. August

Hope to see you there!

On behalf of the organizersSenja Barthel, Riya Dogra, Stavroula Makri, Hannah Santa Cruz Baur

From Iris Yoon:

Wesleyan University is hiring a visitor. The teaching load is 2-1, and it’s a “1 + 1” position, meaning that the initial contract is 1 year but may be renewed for another year if performance is satisfactory. The deadline is April 10.  

https://www.mathjobs.org/jobs/list/28241

The Department of Mathematics at the University of Florida is looking to fill one Visiting Assistant Professor position, beginning August 16, 2026. Please apply by March 22, 2026.

https://www.mathjobs.org/jobs/list/28154

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