Author: Mikael Vejdemo-Johansson

This group is close to Wojciech Chacholski and the Stockholm Topological Data Analysis research groups.

KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as in architecture, industrial management, urban planning, history and philosophy.

Job description

The Department of Mathematics at KTH is offering two-year post-doctoral positions within the Brummer & Partners MathDataLab. The Brummer & Partners MathDataLab is a research lab in mathematics and applied mathematics, hosted at the Department of Mathematics, that aims at creating a hub for mathematical research in the analysis of complex data. The Brummer & Partners MathDataLab supports top talent among junior researchers by offering competitive postdoc positions, and aims to stimulate collaboration between existing faculty and surrounding institutions. A further aim is to inspire and facilitate the education of a new generation of mathematicians focused on foundations and implementations of novel methods for data analysis. The post-doctoral positions at the MathDataLab aims at conducting research in mathematics (e.g. topology, analysis, combinatorics, etc) or applied mathematics (mathematical statistics, numerical analysis, optimisation, etc) with emphasis on development of theory and/or methods for data analysis. The positions are linked to projects that are described in detail at the webpage: https://www.kth.se/math/datalab

What we offer

International workplace.
A leading technical university that creates knowledge and expertise for a sustainable future.
Here you get colleagues with high ambitions in an open, curious and dynamic environment.
An inspiring research environment in mathematics and applied mathematics.

Qualifications

A PhD degree, awarded (or planned to be awarded before the commencement of the position) within the last 3 years in mathematics, applied mathematics, or a closely related area is a requirement. We seek a candidate with a strong background in parts of mathematics relevant to the research activity of one or more of the proposed projects. The successful applicant should be strongly motivated, have the capability to work independently as well as in collaboration with members of the research group, and have good communication skills. No skills in Swedish are required.

Requirements

A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline.

Preferred qualifications

Great emphasis will be placed on scientific ability as well as personal competence and suitability. Preferred qualifications include, in addition, ability to collaborate, independence, and pedagogical skills.

Trade union representative

You will find contact information to trade union representatives at KTH:s webbpage.
https://intra.kth.se/en/administration/rekrytering/annonsering/fackrepresentanter-1.500898

Application

Log into KTH’s recruitment system in order to apply to this position. You are the main responsible to ensure that your application is complete according to the ad. The application must include: <br<CV including relevant professional experience and knowledge.
Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any of these languages.
Brief account of why you want to conduct research, your academic interests and how they relate to your previous studies and future goals. Max two pages long.
Brief motivation of the project/projects that you are interested in, OR own research plan.
Two letters of recommendation, with subject: “MDL Letter of recommendation” sent to jobs@math.kth.se
Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time).

Link to log in and apply

https://kth.varbi.com/en/what:login/jobID:298671/type:job/where:4/apply:1/?_ga=2.45146212.1367306853.1573455645-1415105998.1552374180

The Department of Mathematics at the University of Western Ontario has a postdoctoral position available in Topological Data Analysis, under the supervision of J.F. Jardine.

This position has a two-year term with a flexible start date of July 1, 2020. The salary will be $51,000 CDN per year, plus a tax-free research fund of $1,500 per year. The position will involve teaching two half-courses per year, in addition to research. Candidates should have completed a Ph.D. in July 2017 or later. The filling of the position is subject to budgetary considerations.

All applications should include a cover letter, a curriculum vitae (including a list of publications), research statement, teaching statement, and at least three letters of reference. One letter of reference should comment on the teaching abilities of the applicant.

https://www.mathjobs.org/jobs/jobs/15179

Liz Munch is hiring a joint postdoc with Dan Chitwood in the CMSE department at MSU for projects related to applying TDA to 3D voxel images for quantifying plant morphology.  Applications are due Dec 16, 2019, and more info is here.  We expect the successful candidate to begin Aug 2020.

[Note: Union College houses among others Ellen Gasparovic, who does TDA]

On behalf of the Department of Mathematics at Union College, I am writing to make you aware of openings for a tenure-track position and for two visiting positions in our department starting in September 2020. The details are available at https://www.mathjobs.org/jobs?joblist-195-14758.

The mathematics department and Union College value student and workforce diversity.  We are committed to continue developing as a community of diverse populations and cultures including, but not limited to, those based on race, religion, disability, ethnicity, sexual orientation, gender, gender identity, national origin and veteran status. As such, we are always looking to diversify our applicant pool so that it is as broad as possible.  Toward this end, we would be grateful if you could let those you know who are on the job market know about our positions.

I would also like to provide you (and prospective applicants) with some additional information about our college and department.  Union is a liberal arts college with engineering located in Schenectady, NY, part of the Capital District of New York State.  Union is an historic college, having been founded in 1795 as the first non-denominational college in the U.S. Our mission is to develop in our students the analytic and reflective abilities needed to become engaged, innovative, and ethical contributors to an increasingly diverse, global, and technologically complex society. This past year, the College celebrated the inauguration of our 19th president, David Harris, who is challenging us to learn to be more comfortable with being uncomfortable in the service of personal and communal growth and wisdom.  We are part of a metropolitan area of more than a million people with proximity to major cities and outdoor recreation; specifically, we are convenient to Boston, Montreal, and New York City (3-hour drive to each plus frequent Amtrak service to NYC) as well as the Adirondack Park and Vermont.

Faculty members at Union are focused both on teaching undergraduates and on research. Our department, with twelve tenure-track faculty lines, has a welcoming, supportive, and collegial environment.

Again, we would be grateful if you could let those you know who are on the job market know about our positions (and please feel free to forward this email to them).

Best wishes,

Christina Tønnesen-Friedman

Math Department and Hiring Committee Chair

Júlia Borràs Sol writes:

We are searching for a PhD student to work on topics related to computational topology, geometry, and robotics. In particular, we are part of an ERC European project (https://clothilde.iri.upc.edu/) focused on defining the mathematical fundaments of cloth manipulation using robots. The proposed PhD Thesis would work on exploring topological indexes, like for instance, the Gauss Linking Integral that measures the level of writhe between two curves in the space. This has been used as a guide for path planning in robotics, and we want to extend its application to bi-manual manipulation in general, and cloth manipulation if possible.

IRI is a robotics institute in Barcelona with a team of international researchers on robotics, we are part of a dynamic group (https://www.iri.upc.edu/research/perception) that offers many further opportunities, and nice applications for our theoretical studies.

Candidates must be doing or have a master’s degree. Please, contact us urgently if interested.

Thesis title: “Topological measures to plan flexible objects bimanual robotic manipulation”
Advisors: Júlia Borràs and Maria Alberich
Reference: MDM-2016-0656-19-1
Related project: MdM: Unit of Excellence María de Maeztu
More info: https://www.iri.upc.edu/jobs/77
Contact: jobs@iri.upc.edujborras@iri.upc.edu

Patrick Shafto writes:

We have a postdoc opening at Rutgers Newark. Expertise in TDA would be especially valuable!
https://www.mathjobs.org/jobs/jobs/15072

Kevin Knudson writes:

The University of Florida Department of Mathematics is hiring two tenure-track faculty in data science, broadly construed. Come work with us!

https://www.mathjobs.org/jobs/jobs/15032

With the framework of the International Training Network CANCERPREV, Kathryn Hess will supervise a PhD student to work on a project concerning “Detection of cyclic changes in gene expression by topological data analysis”.   The student will most probably be affiliated with the new PhD program in computational biology at EPFL in Lausanne (Switzerland).

Interested potential candidates are encouraged to contact Kathryn Hess for more information.  The application deadline is December 15.  Further information about how to apply can be found here. 

Dear Colleagues,

We invite you to submit your latest research in the area of applied and computational topology to this Special Issue, “Topological Data Analysis”. We are looking for new and innovative approaches to use methods from algebraic topology in data analysis, statistics, and machine learning. This Special Issue is intended to feature a balance between theoretical developments in topological data analysis and practical applications. Topics include but are not limited to persistence theory, multidimensional persistence, design of filtered simplicial complexes from data, summaries of persistence modules, design of new algorithms to efficiently use topological insights in data science applications, as well as a broad spectrum of applications of topological methods in robotics, biology, medicine, and social sciences. 

For more details, see the website https://www.mdpi.com/journal/algorithms/special_issues/Topological_Data_Analysis

Nello Blaser
Guest Editor

L2F – Learn to Forecast, the Laboratory for Topology and Neuroscience (EPFL, Switzerland) and the Institute of Reconfigurable and Embedded Systems (heig-vd, Switzerland) are excited to announce Giotto, an open-source project aimed at integrating topological data analysis and machine learning at a fundamental level.

Giotto’s objective is to bring topological data analysis closer to the broader data science community, and to gather contributions from experts in the field.

Our first product is the Python library giotto-learn, released on 21 October 2019 under the Apache 2.0 license. We put an emphasis on making giotto-learn intuitive, user-friendly, and performant. It offers a convenient API and is fully compatible with the most used all-purpose machine learning library in the world, scikit-learn.

giotto-learn inherits the modularity and flexibility of the scikit-learn framework and extends the latter’s reach to include steps inspired by topological data analysis and by the theory of dynamical systems. The ability to create complex pipelines and to use scikit-learn’s model selection and hyperparameter searches, allows for topology-informed machine learning to be performed at larger scales and in the style used in modern data science. Our collaboration’s first paper shows how this allows for an extensive topological analysis of the MNIST digits dataset, including successful classification using topological features only!

While the API is written in Python, the package incorporates compiled C++ code for efficiency. In v0.1.0, Ripser (newly bound to our Python code) is used for fast computation of Vietoris-Rips persistence, and an optimised version of Hera is used for bottleneck and Wasserstein distances.

We look forward to your comments, suggestions and merge requests! Giotto’s core team is happy to help and can be reached at maintainers@giotto.ai.