Category Archives: appliedtopology

PhD position in TDA at Swansea University.

As part of the major new Oxford-Swansea-Liverpool Center for Topological Data Analysis (funded by EPSRC grant EP/R018472/1), we are looking for a PhD student to join the Swansea team in investigating applications of topology to data science and physics.

Our team consist of:
Dr Pawel Dlotko - interested in applied and computational topology and data analysis.

Dr Jeffrey Giansiracusa -interested in topology and tropical algebraic geometry.

Prof. Biagio Lucini -interested in computational physics and quantum theory.

A postdoc with research interests in topological data analysis.

Multiple PhD students

The precise focus of the project will be adapted to the interests and background of the successful candidate. Potential emphasis could be in one or more of the following: new computational methods in topological data analysis, algebraic/geometric and category theoretic aspects of topology, topological analysis of phase transitions and topological objects in quantum field theory and other systems.

For more details please consult:

Do you have any questions? Please let us know:

Jeffrey Giansiracusa (

Pawel Dlotko (

Summer School: TDA and Persistent Homology

Topological Data Analysis and Persistent Homology - First Announcement

A school devoted to Topological Data Analysis and Persistent Homology will take place from Monday, June 11 to Friday June 15, 2018, at the Hotel Bellavista in Levico Terme (Trento, Italy), in the framework of the scientific activity of CIRM-FBK (

The program consists of three mini-courses delivered by John Harer (Duke University), Steve Oudot (INRIA Saclay) and Christopher J. Tralie (Duke University).

For details we refer to the official webpage of the school, now published at the link

Some funds to cover living expenses for young participants are available.

The deadline for registration and application for financial support is April 30, 2018.

PhD position at Tulane in TDA for Digital Pathology

Carola Wenk writes
I have an opening for a PhD position in the use of topological descriptors and HPC methods for digital pathology, see below.

A PhD research assistantship in visualization and computational topology of biomedical data is available in the Department of Computer Science at Tulane University under the supervision of Brian Summa and Carola Wenk, part of the NSF-funded project "Quantifying Morphologic Phenotypes in Prostate Cancer - Developing Topological Descriptors for Machine Learning Algorithms". See here for more information on the project:
This is an interdisciplinary project including faculty and students from Tulane University and Montana State University in the areas of Mathematics, Computer Science, Biomedical Engineering, and Pathology.

The focus of this PhD research assistantship is on the visualization and high-performance computing aspects of topological descriptors computed on gigapixel image data. This research assistantship is for three years of the typically 5-year PhD program in Computer Science, starting in Fall 2018.

For more information and to apply please contact Brian Summa ( or Carola Wenk ( See here for more information and application instructions for Tulane's Computer Science PhD program:

Postdoc in TDA at Michigan State University

Elizabeth Munch writes:
I am hiring a postdoc in topological data analysis with an emphasis on Reeb Graphs, mapper, and the interleaving distance to start in the fall of 2018. The successful applicant will have a strong math and/or theoretical computer science background, as well as comfort with programming and implementation.

More information and how to apply can be found here :

Of course, feel free to email me with any questions at

Job opening in Applied and Computational Topology advertised by the Queen Mary, University of London

From Michael Farber:

Dear colleagues,

I want to attract your attention to the job opening in Applied and Computational Topology advertised by the Queen Mary, University of London (Lecturer/Senior Lecturer in Applied and Computational Topology - QMUL13442), see

The salary range is £40,865 - £60,109.

Closing date: 11 January, 2018.

PhD studentship at KTH Royal Institute of Technology

Doctoral student in Machine Learning
KTH Royal Institute of Technology, School of Computer Science and Communication

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.

Department information

KTH Computer Science and Communication (CSC) announces PhD positions in Machine Learning at the department of Robotics, Perception and Learning (RPL)

Job description

The scientific work will be conducted along either of the following research directions:

1) Geometric and Topological Methods for Machine Learning with applications to Robotics

Topological Data Analysis is a recently emerging sub-branch of machine learning that enables inference about the global structure of datasets based on rigorous mathematical theory with origins in Algebraic Topology. The research under this theme will focus on developing new geometric and topological techniques for machine learning with a focus on potential application areas in robotics. Possible applications of Geometric and Topological Data Analysis in Robotics include reasoning about robot configuration spaces and free space. This could include development of approaches to autonomously detect unsafe configurations in a self-driving car scenario and to understand how compact components of the free space can be utilized to enable new types of robot manipulation interactions by means of the concept of "Caging". A second potential sub-thread is to investigate how Topological Data Analysis may be of use to analyze representations of data determined by Deep Learning Algorithms. The research will be supervised by Florian Pokorny, Assistant Professor at RPL.

2) Data-driven scene understanding and control in Human-Robot collaborative settings

Future robotic applications are believed to a greater extent include collaboration with humans, humans that do not necessarily have a technical background. Interaction between human and robot thus need to be in a manner that the human finds natural. A collaborative robot should adapt to changes in the environment and tasks that are placed on it. It needs to be in constant learning mode and gradually adjust its behaviours given feedback from both its sensory system and the human collaborator. Research under this theme will focus on a combination of deep learning for scene understanding and generative action modelling, with reinforcement learning applied for control. Emphasis will be placed on methods with which a human can teach a robot the best way of solving a particular task, either through demonstration or by physically guiding the robot. The research will be supervised by Mårten Björkman, Associate Professor at RPL.

This is a four-year time-limited position that can be extended up to a year with the inclusion of a maximum of 20% departmental duties, usually teaching. In order to be employed, you must apply and be accepted as a doctoral student at KTH.

Data science (especially topology position at The Henry M. Jackson Foundation


Position Description
Data Scientist

Position No: FLSA Status: Exempt
Grade: EEO Category/Job Group:

JOB SUMMARY We are seeking a Data Scientist to join the Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO). ACESO aims to identify host-based markers capable of accurately diagnosing and prognosing patients with severe infections in austere settings and transitioning those markers to point-of-care assay platforms. The Data Scientist is responsible for analyzing complex data and developing insights through the use of statistical models, data mining, and data visualization techniques.

This position is based at The Henry M. Jackson Foundation (HJF) in Bethesda, Maryland, although alternate arrangements will be considered. HJF provides scientific, technical and programmatic support services for the worldwide ACESO program.


1. Analyzes complex datasets including RNA sequence data, proteomic, phosphoproteomic, and metabolomics data. Applies advanced statistical and predictive modeling techniques and data visualization approaches. Develops innovative approaches to answer research questions.

2. Integrates and prepares large datasets, develops specialized database and computing environments as needed.

3. Provides subject matter expertise as needed, including recommendations on data collection and integration.

4. Communicates results on a regular basis with the science team and key stakeholders, and prepares presentations and reports as needed.

5. Performs other duties as required.

Required Knowledge, Skills, and Abilities:
 Experience with complex datasets
 Proficiency in statistical analysis, forcasting/predictive analytics, and algorithm optimization.
 Experience with data mining/pattern recognition approaches; experience with topological data analysis preferred
 Strong programming skills
 Able to develop solutions to loosely defined problems
 Able to communicate effectively

Minimum Education/Training Requirements: PhD in mathematics, statistics, computer science or related field. At least 2 years relevant experience.

Physical Capabilities: Extended periods of sitting

Required Licenses, Certification or Registration: n/a

Supervisory Responsibilities/Controls: May provide guidance to junior analysts

Work Environment: Office or laboratory environment

Any qualifications to be considered as equivalents, in lieu of stated minimums, require the prior approval of the Director of Human Resources

Tenure track job opening in TDA at the University of Oklahoma

MathJobs Site:

Departmental Site:

The Department of Mathematics at the University of Oklahoma is experiencing an exciting multi-year period of growth and development. We are seeking to expand upon the strengths of our Geometry and Topology groups and to develop a program in Computational Geometry or Applied Topology. We encourage dynamic and innovative individuals to apply for a full-time, tenure-track position at the Assistant Professor level in Computational Geometry or Applied Topology beginning August 2018. A higher rank appointment may be considered in exceptional circumstances.

Normal duties consist of teaching two courses per semester, conducting research, and rendering service to the department, university, and profession.


The position requires an earned doctorate and research interests that complement and extend the strengths of the department. Current teams in the department include: functional and geometric analysis, partial differential equations and dynamical systems, numerical analysis, automorphic forms and number theory, representation theory, geometric group theory, topology, Riemannian geometry, and research in undergraduate mathematics education.

This is a new position intended to open new horizons in mathematical research especially bridging the gap between topology/geometry and data science. We seek strong candidates with proven expertise in the emerging areas of computational topology, topological data analysis, computational geometry and geometric inference among others. We invite exceptional candidates in these areas whose research interests may include a strong computational component working with data to apply. The department intends to grow this area with more hires expected in the coming years. This initiative also dovetails with a larger initiative by the university to hire in areas that combine traditional faculty lines with data science: at least two searches are being conducted in parallel in digital humanities and computational neurobiology at the college level which are intended to bolster the university’s commitment to programs in big data and data science.

Preference will be given to applicants with postdoctoral experience and with a demonstrated potential for excellence in research and teaching.

In addition to interacting with faculty in the department, the successful candidate will have the opportunity to work on interdisciplinary projects with researchers around campus with needs in analyzing large data sets.

Job Opening in Topological Data Analysis at Florida Atlantic University

Math Jobs add:

FAU Jobs website:

The Department of Mathematical Sciences at Florida Atlantic University invites applications for a tenure-track position at the assistant professor level in the area of topological data analysis, starting in August 2018.

The successful candidate will be expected to pursue research that complements current expertise in the department, which includes applications of computational homology to dynamical systems and topology of random manifolds. Research areas of particular interest for this position include, but are not limited to, mathematical foundations of TDA, geometric and topological methods in data science, computational topology, and interdisciplinary applications. Ideally the successful candidate will broaden the scope of mathematical research in these areas, forming collaborations within the department as well as conducting interdisciplinary research.

Responsibilities for this position will be teaching, scholarly research, and professional service. For additional information about the position, please contact the Chair of the Search Committee by email to

The Department of Mathematical Sciences at FAU offers a full range of undergraduate and graduate degree programs in mathematics. The department has more than forty full-time faculty members, approximately two-thirds in tenure-earning positions, and nearly fifty doctoral students. FAU is home to The Center for Cryptology and Information Security and The Center for Complex Systems and Brain Sciences. Both the Scripps Research Institute and the Max Planck institute have branches located near the Jupiter campus.

Applicants must possess a Ph.D. in Mathematics or a closely related field. Candidates in all areas of topological, geometric, and high-dimensional data analysis will be considered.

The successful candidate will be expected to teach effectively and direct research at both the undergraduate and graduate level, participate in interdisciplinary programs, and apply for external research funding.

The salary range is $65,000 - $75,000. For additional information about the position, please contact us by email to

This position is open until filled and may close without prior notice. Priority consideration will be given to applications received by January 1, 2018.

All applicants must apply electronically to the currently posted position on the Office of Human Resources' job website ( by completing the Faculty, Administrative, Managerial & Professional Position Application and submitting the related documents. The position number that should be referenced while applying is #981754.

In addition, please arrange to have three letters of recommendation sent by first class mail to: Chair of the Search Committee, Department of Mathematical Sciences, Florida Atlantic University, 777 Glades Rd., Boca Raton, FL 33431 or by email to

A background check will be required for the candidate selected for this position.

Florida Atlantic University is an equal opportunity/affirmative action Institution, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. Individuals with disabilities, requiring accommodation, please call (561) 297-3057 - TTY 711.