• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer
  • Bluesky
  • Facebook
  • Instagram
  • Twitter
  • YouTube
CDE Almería – Centro de Documentación Europea – Universidad de Almería

CDE Almería - Centro de Documentación Europea - Universidad de Almería

Centro de Documentación Europea de la Universidad de Almería

  • HOME
  • WHAT´S ON
    • EU NEWS
    • Activities
    • EU Calls and Awards
    • Radio Program «Europe with You»
  • DOCUMENTATION
    • EU Media Collection
      • Web Space
      • MEDIATHEQUE REPOSITORY
  • Europe on the net
    • Institutions
    • EU Representation in Spain
    • European information network of Andalusia
  • ABOUT US
    • Presentation
    • Services
    • People
    • Contact
  • Spanish
  • English

Postdoc in robust machine learning

Inicio » EU Calls and Awards » Euraxess » Engineering and Architecture » Postdoc in robust machine learning

23 de June de 2020

We invite candidates to apply for one postdoc position funded by The Knut and Alice Wallenberg Foundation through The Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest ever individual research program, and a major national initiative for strategic basic research, education and faculty recruitment. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society as well as industry.

 

This project aims to design and implement robust learning and data-centric optimization techniques for advancing state-of-the-art machine learning algorithms where data is geographically distributed, sensitive, and scarce. Robust machine learning and data-centric optimization algorithms empower models through multi-level (local, global and hybrid) training, learning, and inference with data-centric optimization for scarce data and non-standard model settings. By creating unique features (e.g., decentralized training, learning and inference, fault-tolerant against failures and attacks, data-centric optimization, robustness), this project addresses the challenges in the following areas: robust learning; learning with scarce data and non-standard model settings; lack of theoretical knowledge to build manual models; computation efficient learning and optimization for obtaining more accurate and robust models with applications to constraint environments (i.e., Industrial Internet of Things (IIoT), healthcare systems) and edge infrastructures.

Qualifications

Applicants must have earned a PhD or a foreign degree that is deemed equivalent to a PhD in Artificial Intelligence, Machine Learning or Optimization for Machine Learning, Computer Science or a subject relevant for the position. The PhD degree should not be more than three years old by the application deadline, unless special circumstances exist.

Since research is conducted in an international research environment, the ability to collaborate and contribute to teamwork, and an excellent command of the English language, both written and spoken, are essential requirements.

We particularly invite female candidates to apply to ensure gender balance.

Specific Requirements

Candidates are expected to have outstanding knowledge of machine learning and optimization techniques. Demonstrable knowledge of data wrangling and learning in decentralized settings is a prerequisite. Experience in any of the areas robust learning, fault-tolerant learning and data-centric optimization when data is geographically distributed, sensitive and scarce is a merit.

Application

The application must be written in English or Swedish. Documents must be in Word or pdf format.

  • Introductory letter including a 2-page statement of research interests relative to the above topics and a motivation of why your expertise is appropriate for the position.
  • Curriculum Vitae (CV) including a complete list of scientific publications.
  • Copies of degree certificates, including documentation of completed academic courses and obtained grades
  • A copy of your PhD thesis and copies of (max 5) original research publications relevant to the above topics, numbered according to the publication list.
  • Names and contact information for three persons willing to act as references.
  • Any other information relevant for the position such as description of software development experience, or previous industry experience.

Organisation

Umea University

Research Field

Computer science › Computer systems

Location

Sweden › Umea

Deadline

10 August 2020

More information

Euraxess

Publicaciones relacionadas:

3 Post-doctoral research fellowships open to candidates from all countries and all disciplines in Australia Professor/Associate Professor in Artificial Intelligence Postdoctoral researcher position within the Quantum Biology Tech (QuBiT) Lab at UCLA Ph.D. in Numerical Modeling and Simulation for Subsonic and Supersonic Combustion in Canada Post-doctoral position in quantum machine learning and quantum artificial intelligence

Engineering and Architecture,  EU Calls and Awards,  Euraxess,  Science call,  Euraxess,  software,  Sweden

“This is a space for debate. All comments, for or against publication, that are respectful and do not contain expressions that are discriminatory, defamatory or contrary to current legislation will be published”.

Reader Interactions

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Primary Sidebar

Footer

  • CDE Almería
  • Biblioteca Nicolás Salmerón – Universidad de Almería
  • Planta: 1ª, Despacho: 1.05.0B.
  • Ctra. Sacramento s/n. Almería (Spain)
  • Teléfono: (+34) 950 015266

HOME
NEWS
DOCUMENTATION
EUROPE ON THE NET
ABOUT US

  • LEGAL NOTICE
  • PRIVACY POLICY
  • COOKIE POLICY
  • ACCESSIBILITY
  • SITEMAP

Copyright © 2026 CDE Almería · Creative Commons LicenseThis work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

<p>El Centro de Documentación Europea de la Universidad de Almería utiliza cookies propias y de terceros para facilitar al usuario la navegación en su página Web y el acceso a los distintos contenidos alojados en la misma. Asimismo, se utilizan cookies analíticas de terceros para medir la interacción de los usuarios con el sitio Web. Pinche el siguiente enlace si desea información sobre el uso de cookies y como deshabilitarlas. </p>

Politica de privacidad

El Centro de Documentación Europea de la Universidad de Almería utiliza cookies propias y de terceros para facilitar al usuario la navegación en su página Web y el acceso a los distintos contenidos alojados en la misma. Asimismo, se utilizan cookies analíticas de terceros para medir la interacción de los usuarios con el sitio Web. Pinche el siguiente enlace si desea información sobre el uso de cookies y como deshabilitarlas. <a href="/politica-de-cookies" rel="noopener" target="_blank">Más información</a>

Cookies estrictamente necesarias

Las cookies estrictamente necesarias tiene que activarse siempre para que podamos guardar tus preferencias de ajustes de cookies.

Básicamente la web no funcionara bien si no las activas.

Estas cookies son:

  • Comprobación de inicio de sesión.
  • Cookies de seguridad.
  • Aceptación/rechazo previo de cookies.
Cookies de terceros

Esta web utiliza Google Analytics, Google Tag Manager y Yandex Metrika para recopilar información anónima tal como el número de visitantes del sitio, o las páginas más populares.

Dejar estas cookies activas nos permite mejorar nuestra web.

Política de cookies

Pinche el siguiente enlace si desea información sobre el uso de cookies y como deshabilitarlas. Más información