Overview

we are looking for a PhD student to work on Information Retrieval and
Knowledge Representation. The PhD degree is taking place at TU Wien,
Faculty of Informatics. If your profile fits the description below and
are interested, please send your CV and application documents at
Email

PhD position in Information Retrieval – (f/m/d)

30 hours/week (3 years)

Your profile:

You have a university degree in Computer Science and you meet the
relevant criteria of the TU Wien doctoral programme
(https://informatics.tuwien.ac.at/doctoral/).

Company:

TU Wien

Qualifications:

Knowledge on Information Retrieval, Machine Learning, Text Analysis
Programming / prototyping skills in Java and/or Python. Other
programming languages are a bonus.
Working with and querying databases, code sharing, issue tracking
(JIRA, GIT).
Publications are of advantage
Excellent English communication skills, both written and verbal
(e.g. IELTS at 7.0 or higher)

Your field of activity:

Working in an international research project of the Research Studio
Data Science and towards obtaining a PhD from TU Wien, Faculty of
Informatics.
Independently and collaboratively designing Information Retrieval
and Extraction experiments.
Training and testing hypotheses, principles and models, including
AI/ML models.
Co/authoring research papers, reports and funding bids.
Presenting y/our research at conferences, workshops and public events.

Your personal abilities and qualities:

Understanding of project aims and specific tasks, reporting and
communicating in English.
Ability to proactively seek solutions to complex problems without
needing to be micromanaged
Ability to plan and prioritise own workload and forward plan
Ability to do science systematically, with integrity and to follow
good research practices
Team player able to work to challenging targets
Knowledge of German or willingness to learn
Working in a Linux environment (deployment, essential scripting,
configuration, logging, etc.).

The 3-year (1 + 2) PhD contract will be awarded on a first come first
serve basis to the first suitable candidate. Female candidates and
candidates with minority backgrounds are highly encouraged to apply.

Educational level:

Master Degree

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