12/06/2020
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PhD students and Postdocs: Representation Learning for Planning in AI

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  • ORGANISATION/COMPANY
    Universitat Pompeu Fabra - ETIC
  • RESEARCH FIELD
    Computer science
  • RESEARCHER PROFILE
    Recognised Researcher (R2)
  • APPLICATION DEADLINE
    15/07/2020 15:00 - Europe/Athens
  • LOCATION
    Spain › Barcelona
  • TYPE OF CONTRACT
    Temporary
  • JOB STATUS
    Full-time
  • HOURS PER WEEK
    37,5
  • OFFER STARTING DATE
    01/10/2020
  • EU RESEARCH FRAMEWORK PROGRAMME
    H2020 / ERC

OFFER DESCRIPTION

Research on representation learning for planning in AI

Doctoral and Postdoctoral Openings in Artificial Intelligence at UPF

in context of the research project RLeap: Representation Learning for Planning

Funded by an Advanced ERC Grant (2020-2025).

PI: Hector Geffner, ICREA and UPF, Barcelona

We have several funded slots for doctoral students and postdoctoral researchers at the AI and ML group at the Universitat Pompeu Fabra, Barcelona, Spain to carry out research on Representation Learning for Planning.

The project addresses a research problem that is at the heart of the current split in AI between data-based learners and model-based reasoners: the problem of learning symbolic representations from raw perceptions.

In our case, first order symbolic representations, involving objects and relations, are to be learned from scratch for planning and generalized planning.

Other dimensions of representation learning to be pursued in the project include representation grounding, transfer, composition, and scaffolding.

We are seeking highly motivated doctoral students and postdoctoral researchers eager to make a difference in these problems, with experience in areas such as

machine learning, planning, logic and knowledge representation, combinatorial optimization and SAT.

Ideal candidates should be able to do or learn to do theoretical and experimental work, logic and algorithms, and programming and "differential programming" (deep learning. .Good oral and written skills in English are required.

The funds come from an Advanced ERC Grant (RLeap: From Data-based to Model-based AI: Representation Learning for Planning), the EU funded TAILOR network (Trustworthy AI: Integrating Learning, Optimization and Reasoning), and a grant from the Wallenberg (KAW) Foundation and Swedish WASP program in AI.

The *deadline for PhD students* is July 10th. For Postdocs, there is no deadline and the search for qualified candidates will continue until the slots are filled.

Interested PhD candidates should send a CV, transcripts, three reference letters, and a motivation statement to:

rleap.artint@gmail.com.

Postdocs should send a CV, contact details of three references, and a research statement.

We are flexible to alleviate effects of COVID-19, with the possibility of working remotely while needed, once the working documents are ready.

More details about the research can be found at: http://www.dtic.upf.edu/~hgeffner/rleap.html

 

More Information

Offer Requirements

  • REQUIRED LANGUAGES
    ENGLISH: Excellent

Skills/Qualifications

Required education Level: Phd or equivalent

Doctoral and Postdoctoral Openings in Artificial Intelligence at UPF in context of the research project RLeap: Representation Learning for Planning Funded by an Advanced ERC Grant (2020-2025). PI: Hector Geffner, ICREA and UPF, Barcelona We have several funded slots for doctoral students and postdoctoral researchers at the AI and ML group at the Universitat Pompeu Fabra, Barcelona, Spain to carry out research on Representation Learning for Planning. The project addresses a research problem that is at the heart of the current split in AI between data-based learners and model-based reasoners: the problem of learning symbolic representations from raw perceptions. In our case, first order symbolic representations, involving objects and relations, are to be learned from scratch for planning and generalized planning. Other dimensions of representation learning to be pursued in the project include representation grounding, transfer, composition, and scaffolding. We are seeking highly motivated doctoral students and postdoctoral researchers eager to make a difference in these problems, with experience in areas such as machine learning, planning, logic and knowledge representation, combinatorial optimization and SAT. Ideal candidates should be able to do or learn to do theoretical and experimental work, logic and algorithms, and programming and "differential programming" (deep learning. .Good oral and written skills in English are required. The funds come from an Advanced ERC Grant (RLeap: From Data-based to Model-based AI: Representation Learning for Planning), the EU funded TAILOR network (Trustworthy AI: Integrating Learning, Optimization and Reasoning), and a grant from the Wallenberg (KAW) Foundation and Swedish WASP program in AI. The *deadline for PhD students* is July 10th. For Postdocs, there is no deadline and the search for qualified candidates will continue until the slots are filled. Interested PhD candidates should send a CV, transcripts, three reference letters, and a motivation statement to: rleap.artint@gmail.com. Postdocs should send a CV, contact details of three references, and a research statement. We are flexible to alleviate effects of COVID-19, with the possibility of working remotely while needed, once the working documents are ready. More details about the research can be found at: http://www.dtic.upf.edu/~hgeffner/rleap.html

Specific Requirements

 

We are seeking highly motivated doctoral students and postdoctoral researchers eager to make a difference in these problems (https://www.dtic.upf.edu/%7Ehgeffner/rleap.html), with experience in areas such as machine learning, planning, logic and knowledge representation, combinatorial optimization and SAT.

Career Stage:  Early stage researcher or 0-4 yrs( Post graduate)

Work location(s)
4 position(s) available at
Universitat Pompeu Fabra
Spain
Barcelona
Barcelona
Barcelona

EURAXESS offer ID: 531813

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