All posts by Mikael Vejdemo-Johansson

Postdoc at Michigan State University

Two NSF/NIH funded postdoc positions are available in the following fields:

-Computational or applied topology/geometry/graph/algebra

-Machine learning/deep learning

-AI-based drug design and discovery

-Computational biophysics

Ideal candidates should have experience in code development, have demonstrated the potential for excellence in research, and hold a recent Ph.D. degree in either mathematics, computer science, computational biophysics, computational chemistry, or bioinformatics. The selected candidates will be teamed up with top performers in recent D3R Grand Challenges, a worldwide competition series in computer-aided drug design. Salary depends on experience but will be at least $47.5k. The positions enjoy standard faculty health benefit. Please send CV to

Union College Math Conference 2019

2019 Union College Math Conference to be held in Schenectady, NY on the dates Friday Sept 13 - Sunday Sept 15. There will be parallel sessions in: Differential Geometry, Geometric Analysis, and Mathematical Physics; Applied Topology; History of Mathematics; and Number Theory. The plenary speakers are:

Robert Ghrist (University of Pennsylvania)

Carolyn Gordon (Dartmouth College)

Álvaro Lozano-Robledo (University of Connecticut)

John McCleary (Vassar College) 

The website for the conference can be found here: 

Registration is currently open, and the (first) deadline for abstract submission is July 19.

IEEE ICMLA Session on TDA in ML

Dr. Juan Ramirez wants to pass on a call for research papers to the 2019 IEEE International Conference on Machine Learning and Applications.  He is the special session chair for a session called " Topological Data Analysis in Machine Learning". Below is a link of the special session solicitation. Conference papers for this session are due September 7th 2019 and carry a maximum page number of 8 pages.  (

PhD project in ML/TDA for weather and climate

Helwig Hauser writes:

Postdoc: Topology of Neural Networks

Research Fellowship in Topological Complexity of Neural Networks

We are currently advertising a one-year postdoctoral position to start on 1st September which will be based within the School of Mathematical Sciences. This project is supported by the Alan Turing Institute and the University of Southampton, and is devoted to the study of foundational questions regarding the quantification of the complexity of neural networks.

The successful candidate will work in a thriving interdisciplinary research group at Southampton and will have access to the Alan Turing Institute. The details of the position, requirements, and application procedure are given on, with the reference number 1153919PJ. Jacek Brodzki <> would be happy to answer any questions regarding the post. The deadline for applications is 24 July.

Persistence in PyTorch

Primoz Skraba writes:
Announcing a persistent homology layer for PyTorch. The layer takes in either a simplicial complex or a point cloud, computes the persistence diagram and given an energy function automatically backpropogates. This allows for simple integration with other PyTorch modules as well as continuous optimization over persistence diagrams. Our goal is to make experimentation combining topology and deep networks easier and more accessible.

The module along with installation instructions and several examples can be found at

The companion paper describing the examples can be found at

PhD Positions in Applied Algebraic Topology in Aberdeen

PhD positions in Applications of Algebraic Topology to Neuroscience.

Applications are invited for a fully funded studentship in applied algebraic topology. The studentship is funded by a collaboration grant between the Blue Brain Project at EPFL and the University of Aberdeen. The project involves research in algebraic topology, interactions with and applications to neuroscience.

Consideration will be given to applicants who already have or are expecting to have a First Class degree in mathematics or equivalent by the end of this academic year. Preference may be given to candidates with an MSc in mathematics. Some familiarity with applied and computational topology is an advantage but is not formally required.

Applications should be submitted to the University of Aberdeen

Candidates are encouraged to send a CV, a transcript of prior study and a letter of intent by email to Ran Levi at, prior to formal application.

Postdoc in TDA at EPFL

The Laboratory for Topology and Neuroscience (EPFL) and L2F—Learn to Forecast (EPFL Innovation Park) invite applications for two postdoctoral positions in topological data analysis and machine learning, funded by the project “Topological Warning Signals for Critical System Transitions” supported by Innosuisse (Swiss Innovation Agency).

The aim of this project is to develop original predictive methods, combining advances in topological data analysis with machine learning research. The first goal of the project, inspired by critical phase transitions, is to define a new type of early warning signal using applied topology, in order to better anticipate sudden changes of regime such as financial crashes, earthquakes, or epileptic attacks. The second goal concerns the creation of new local features by analyzing the topology of datasets, in order to generalize current topological data analysis techniques to enhance the performance of machine learning models. 

L2F is a research-driven company that offers mathematically sophisticated machine learning solutions to corporate and institutional clients. L2F’s researchers, who won the 2017 NYC Taxi Challenge on Kaggle, are motivated by the desire to understand the fundamental laws of machine learning, in terms of its underlying mathematical theory. L2F is one of the fastest growing Swiss companies, with already 30 employees after one year of existence, and provides an exciting environment for multi-disciplinary researchers.

The appointed candidates will be based at L2F on the EPFL Innovation Park and engage in state-of-the-art research, in collaboration with the Laboratory for Topology and Neuroscience.

Candidates should hold a PhD in one of the following areas: algebraic topology, theoretical physics, or machine learning. Please send your cover letter, CV, and publication list to Kathryn Hess at  and Maxime Gabella at, to whom you should arrange for three letters of reference to be sent as well.

Starting date: March 1, 2019, or as soon as possible thereafter.

Duration: 18 months.

Application deadline: January 1, 2019.

Geometric Data Analysis, U Chicago, May 20-23 2019

Conference on Geometric Data Analysis, May 20-23, 2019, on the University of Chicago main campus in Hyde Park.

This conference will bring together experts from around the world in the combination of geometrical or topological methods with probabilistic and statistical ones for the study of data.  Different ideas have been found valuable in the handling of different kinds of data, and we hope to promote discussions of what works and what fails, and when and why.

Invited Speakers

Yuliy Baryshnikov, Electrical and Computer Engineering, University of Illinois
Mikhail Belkin, Computer Science, Engineering and Statistics, Ohio State University
Paul L. Bendich, Mathematics, Duke University
Omer Bobrowski, Electrical Engineering, Technion, Institute of Technology, Israel
Jeff Brock?, Yale University
Gunnar Carlsson, Mathematics, Stanford University
Daniela Egas Santander, Topology and Neuroscience, Ecole Polytechnique Fédérale de Lausanne, Switzerland
Tamal Krishna Dey, Computer Science and Engineering, Ohio State University
Tingra Gao, Statistics, University of Chicago
Herbert Edelsbrunner, Computer Science and Mathematics, Institute of Science and Technology, Austria
Clément Levrard, Probabilités, Statistique et Modélisation, Université Paris Diderot, France
Mauro Maggioni, Mathematics, John Hopkins University
Facundo Mémoli, Mathematics, Computer Science and Engineering, Ohio State University
Bertrand Michel, Informatique et Mathématiques, Ecole Centrale de Nantes, France
Ezra Miller, Mathematics, Duke University
Sayan Mukherjee, Statistical Science, Duke University
Takashi Owada, Statistiques, Purdue University
Gennady Samorodnitsky, Operations Research and Information Engineering, Cornell University
Benjamin Schweinhart, Mathematics, Ohio State University
Amit Singer, Applied and Computational Mathematics, Statistics and Machine Learning, Princeton University
Jonathan Taylor, Statistics, Stanford University
Katharine Turner, Mathematical Sciences, National University, Australia

? to be confirmed

Details about the conference are available on our website:

• Logistical details re.this 4-day conference (May 20-23, 2019) on the University of Chicago main campus in Hyde Park.

Geometric Data Analysis, 2019: Logistics

• Registration is free and open until May 13, 2019.
• Join our mailing list to receive reminders and updates.

Sign Up Form

Please note:

• Travel funds are available to PhD Students, Postdoctoral Students and Early Career Academics.  Please submit your application ( ) by January 9, 2019.
You will be asked to submit your CV, a brief research statement (up to 250 words), and a brief statement explaining why and how attending this conference will contribute to your research (up to 250 words). In addition, please ask someone who is familiar with your work (your academic advisor or your mentor) to send a brief letter supporting your application to, by January 9, 2019. The letter should be addressed to the GDA 2019 Selection Committee.

• Poster sessions will be organized. If you'd like your poster to be considered, please submit your application ( ) by January 9, 2019.

If you have any questions, please email Sylvie at

We hope to see you in May!

Scientific Committee: Robert Adler (Technion), Frederic Chazal (INRIA), Shmuel Weinberger (Chicago)