[agents] [jobs] Two open tenure-track positions in AI (VU Amsterdam)

[Koen Hindriks]

The Computer Science department at the Vrije Universiteit Amsterdam is
looking to hire two tenure-track assistant professors in the field of
Human-Agent Interaction and Collaborative AI. Please consider applying or
help spreading the word in your networks.

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*Human-Agent Interaction opening (apply here
<https://workingat.vu.nl/ad/tenure-track-position-in-human-agent-interaction/wo6om4>)*

Are you an AI researcher and is your aim to research new AI techniques for
human-agent interaction? Do you have a passion for teaching AI? Then Vrije
Universiteit Amsterdam (VU) would like to get to know you. Please apply for
this Tenure Track position in Human-Agent Interaction.

Location: AMSTERDAM
FTE: 1

JOB DESCRIPTION
The research of the Social AI group (https://socialai.nl) is aimed at
advancing AI to improve the way humans and machines understand and interact
with each other. Human-agent interaction is essential for such
human-in-the-loop systems. You are passionate about developing Artificial
Intelligence (AI) for facilitating collaboration between humans and
machines, and you have a proven track record in AI. We are looking for
someone who wants to apply cognitive agent technology to develop
multi-agent systems with humans in-the-loop. Your area of expertise is
related to conversational AI, multi-modal interaction, or machine learning
for learning from human interactions. You initiate, perform and supervise
high-quality social AI research that aims to design AI systems that are
social in nature and are able to take human factors into account. You like
to work in an interdisciplinary team and collaborate with colleagues in
related areas of expertise.

Our facilities (used for research as well teaching) include our Social AI
lab with different hardware platforms such as the Nao and Pepper social
robots, smart displays such as Google nest hubs. We are developing a
cloud-based software platform for social interaction (
https://socialrobotics.atlassian.net/wiki/spaces/CBSR/overview).

Your duties

The position includes research, education and management (40%:40%:20%) and
contains among others the following responsibilities:
- acquire and contribute to externally funded research projects of the group
- pioneer research into AI for human-agent interaction
- teach courses in the BSc and MSc AI curriculum and supervise students
- assist in the supervision of PhD students and contribute to the
management of the group
- being a valuable ‘departmental citizen’ and contributing to management
tasks

REQUIREMENTS
- a PhD degree in Computer Science or Artificial Intelligence
- research experience with at least two of the following topics:
    . social robotics or other social interfaces
    . multi-modal interaction
    . machine learning for learning from human interactions
    . adaptive systems
- experience with an engineering approach to problem solving
- published in international journals and conference proceedings of high
quality
- strong communication and cooperation skills and ability to work in a team
- educational skills and willingness to contribute to BSc and/or MSc AI
programs
- experience or good prospects for acquiring external research funding
- excellent command of the English language
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*Collaborative AI opening (apply here
<https://workingat.vu.nl/ad/assistant-professor-tenure-track-collaborative-ai/phv5eg>)*

Do you want to contribute to developing collaborative AI, with a focus on
fundamental research on personalised learning and long-term interaction? Do
you want to work in close collaboration with our colleagues in the other AI
research groups: Computational intelligence, Knowledge Representation and
Reasoning, and Machine Learning? Then please apply for this Assistant
Professor (tenure track) Collaborative AI position at Vrije Universiteit
Amsterdam (VU).

Location: AMSTERDAM
FTE: 0.8 - 1

JOB DESCRIPTION
The research of the Social AI group (https://socialai.nl) aims to create
hybrid AI systems where humans and machines collaborate, machines learn to
adapt on how to interact with their users, and humans and machines teach
each other to improve their individual and joint performance. We maintain a
broad view where humans and machines can adopt the role of the teacher or
the learner and investigate both directions, humans teaching machines and
vice versa, using various applications as test cases. We are particularly
interested in how we can personalize such interactions, by means of
knowledge structures such as a memory of interactions in order to learn
user profiles and ensure interaction remains engaging over time.
Multi-modal perception is key to making effective interactive systems and
expertise in this area is a pre, as is expertise in the design of such
interactions using e.g., conversational AI, (social) robots, or other
adaptive or knowledge-driven interfaces.

Our facilities (used for research as well teaching) include our Social AI
lab with different hardware platforms such as the Nao and Pepper social
robots, smart displays such as Google nest hubs. We are developing a
cloud-based software platform for social interaction (
https://socialrobotics.atlassian.net/wiki/spaces/CBSR/overview).

Your duties

The position includes research, education and management (40%:40%:20%) and
contains among others the following responsibilities:
- performing research in Collaborative AI
- supervising PhD students
- teaching in the Bachelor and Master programmes of the Department of
Computer Science
- supervising MSc/BSc student research projects in the Department
- contributing to and writing research grant proposals
- contributing to administrative tasks

REQUIREMENTS
- a PhD degree in a relevant field and some years of scientific experience
in post-doctoral research
- expertise in AI technologies that can contribute to improving
collaboration between human and machines
- experience in setting up efficient, ethical, human subject studies and
data collection
- interdisciplinary mindset and a good team player; experience in
collaboration across teams, e.g. in large collaborative projects is a pre
- ideally, experience in teaching at BSc or MSc level
- ideally, some experience in PhD supervision
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