Postdoctoral and Research Fellow positions in Artificial Intelligence
Finnish Center for Artificial Intelligence FCAI is searching for exceptional postdoctoral researchers and research fellows interested in tackling challenges in machine learning and in creating artificial intelligence that is data-efficient, trustworthy, and understandable.
FCAI is a vibrant research center for Artificial Intelligence in Helsinki, bringing together the expertise in AI research from both academia and industry. It was initiated by Aalto University, University of Helsinki, and VTT Technical Research Centre of Finland and has a total budget of 250 M€ over the next 8 years.
FCAI is built on the long tradition and track record of decades of pioneering machine learning research in Helsinki. It was recently selected to host one of the first ELLIS (European Laboratory for Learning and Intelligent Systems) units that assemble European top talent in machine learning. In early 2019 FCAI was selected as one of the prestigious Flagships of the Academy of Finland, a status granted to very few selected centers of excellence with high societal impact.
In this call you can apply to one or more of FCAI’s Research Programs and Highlights. We welcome especially applications linking two or more of the research areas together. The deadline for applications is January 27th, 2020.
RESEARCH PROGRAMS and HIghlights
FCAI research agenda is spearheaded by seven Research Programs and five Highlights with multiple research groups involved in each. Highlights exist to make sure the fundamental research in FCAI Research Programs is taken into use. For more information see https://fcai.fi/research/
FCAI Research Programs
Research Program 1: Agile probabilistic AI
Agile probabilistic AI develops an interactive and AI-assisted process for building new AI models with practical probabilistic programming. Read more at https://fcai.fi/agile-probabilistic
Keywords: Probabilistic programming; robust and automated Bayesian machine learning.
Several professors contribute. Coordinating professor: Aki Vehtari
Research Program 2: Simulator-based inference
Simulator-based inference develops methodology for the new AI having efficient, interpretable reasoning capability, by cross-breeding modern machine learning and simulator-based inference. Read more at https://fcai.fi/simulator-based
Keywords: Approximate Bayesian computation ABC; likelihood-free inference; generative adversarial networks (GAN); applications in many fields including medicine, materials design, visualization, and business.
Several professors contribute. Coordinating professor: Jukka Corander
Research Program 3: Next generation data-efficient deep learning
Next generation data-efficient deep learning develops methods which harness the power of deep learning while achieving good results with less training data and in particular less human supervision. Read more at https://fcai.fi/deep-learning
Keywords: Deep reinforcement learning; semi-supervised learning; simulation methods; Bayesian deep learning.
Several professors contribute. Coordinating professor: Arno Solin
Research Program 4: Privacy-preserving and secure AI
Privacy-preserving and secure AI develops the new principles and techniques needed for privacy-preserving machine learning and the tools for building trustworthy and secure AI systems. Read more at https://fcai.fi/privacy-preserving-and-secure
Keywords: Privacy-preserving machine learning; differential privacy; adversarial machine learning.
Several professors contribute. Coordinating professor: Antti Honkela
Research Program 5: Interactive AI
Interactive AI enables AI that people can naturally work and solve problems with, and which demonstrates the ability to better understand our goals and abilities, takes initiative more sensitively, aligns its objectives with us, and supports us. Read more at https://fcai.fi/interactive-ai
Keywords: Interactive machine learning; reinforcement learning and computational rationality; cognitive modelling; probabilistic programming for behavioral sciences.
Several professors contribute. Coordinating professor: Antti Oulasvirta
Research Program 6: Autonomous AI
Autonomous AI: addresses the fundamental challenges of long-term autonomous operation, in particular, how learning and planning can be performed to ensure safe operation over long time horizons. Read more at https://fcai.fi/autonomous-ai
Keywords: Autonomous systems; Reinforcement learning; Model predictive control
Several professors contribute. Coordinating professor: Ville Kyrki
Research Program 7: AI in society
AI in Society focuses on social and ethical dimensions of AI. It deals both with the preconditions of trustworthy and socially acceptable AI and the consequences of uses of AI. It aims to bring together AI research and human sciences to better understand how AI works in organizations and society. Read more at https://fcai.fi/ai-in-society
Keywords: Design and domestication of AI; Understandability of AI; Foresight and responsibility in AI decision-making and robotics; Legitimacy and social acceptability of AI
Several professors contribute. Coordinating professor: Petri Ylikoski
FCAI Highlights
Highlight A: Easy and privacy-preserving modeling tools
Easy and privacy-preserving modeling tools has the main objective to measure and maximize the impact of FCAI research on the process of probabilistic AI development. Read more at https://fcai.fi/modeling-tools
Several professors contribute. Coordinating professor: Arto Klami
Highlight B: APPLICATIONS OF AI IN HEALTHCARE
This highlight creates AI tools to tackle real-world problems in healthcare together with expert collaborators from the respective fields. Read more at https://fcai.fi/ai-health
Application 1: AI for genetics
Application 2: Computational design of vaccines
Application 3: Deep learning for healthcare resource allocation
Several professors contribute. Coordinating professor: Pekka Marttinen
Highlight C: Intelligent service assistant for people in Finland
Intelligent service assistant for people in Finland has a mission to deploy real AI services for wide audience in Finland. The Highlight is directly linked to AuroraAI initiative (https://vm.fi/auroraai). Read more at https://fcai.fi/service-assistant
Several professors contribute. Coordinating professor: Tommi Mikkonen
Highlight D: Intelligent urban environment
Intelligent urban environment focuses on how to combine (i) measurements from natural environment, (ii) simulations, and (iii) modeling in order to, e.g., make decisions in interaction with the user (e.g., "what-if-engines") and to model and understand observed and/or simulated processes. This includes applications of Interactive AI, Agile probabilistic AI and simulators to model measurements and simulator outputs from urban environments. Read more at https://fcai.fi/intelligent-environment
Several professors contribute. Coordinating professor: Kai Puolamäki
Highlight E: AI-driven design of materials
AI-driven design of materials develops AI technology for accelerated materials design and characterization. Read more at https://fcai.fi/materials
Several professors contribute. Coordinating professor: Patrick Rinke
There are also many other projects that you can apply to in this call. For additional topics see: https://www.hiit.fi/calls/postdoc-and-research-fellow-postions-winter-2019-2020/
Interested in applying?
Please read more about application details and submit your application following the link below.