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HICT: Doctoral Candidate in Deep Representation Learning – Foundations and New Directions

The Helsinki Doctoral Education Network in Information and Communications Technology (HICT) is a collaborative doctoral education network hosted jointly by Aalto University and the University of Helsinki, the two leading universities within this area in Finland. The network serves as a collaboration platform for doctoral education combining all the relevant subfields of computer science and information technology at Aalto University and the University of Helsinki. It involves at present 80 professors and almost 300 doctoral students, and the participating units graduate altogether more than 40 new doctors each year.

We offer the possibility to join world-class research groups in both universities with multiple interesting research projects to choose from. The list of all open Doctoral Candidate positions in this joint call can be found here:

HICT Doctoral Candidate in Deep Representation Learning – Foundations and New Directions

Supervisor(s): Vikas Garg (Aalto University)

Applications are invited for a PhD position and a Postdoctoral position in deep representation learning, broadly construed. Topics of particular interest include:

(1) Generative Models
(2) Graph Neural Networks
(3) Neural ODEs/PDEs/SDEs, Deep Equilibrium Models, Implicit Models
(4)  Differential Geometry/Information Geometry/Algebraic Methods for Deep Learning
(5) Learning under limited data, distributional shift, and/or uncertainty
(6) Bayesian Methods, Probabilistic Graphical Models, & Approximate Inference
(7) Fair, diverse, and interpretable representations
(8)  Off-policy reinforcement learning, inverse reinforcement learning, and causal reinforcement learning
(9) Multiagent systems and AI-assisted human-guided models
(10) Learning on the edge (i.e., learning under resource constraints)
(11) Applications in physics, computer vision, drug discovery, material design, synthetic biology, quantum chemistry, etc.
(12) Quantum Machine Learning for structured spaces

Representative publications:

(1) John Ingraham, Vikas Garg, Regina Barzilay, and Tommi Jaakkola. Generative Models for Protein Design. NeurIPS (2019).
(2) Vikas Garg, Stefanie Jegelka, and Tommi Jaakkola. Generalization and Representational Limits of Graph Neural Networks. ICML (2020).
(3) Vikas Garg and Tommi Jaakkola. Solving graph compression via Optimal Transport. NeurIPS (2019).
(4)  Vikas Garg, Lin Xiao, and Ofer Dekel. Learning small predictors. NeurIPS (2018).
(5) Vikas Garg, Cynthia Rudin, and Tommi Jaakkola. CRAFT: Cluster-specific assorted feature selection. AISTATS (2016).
(6) Vikas Garg, Adam Kalai, Katrina Ligett, and Steven Wu. Probably approximately correct domain generalization. AISTATS (2021).
(7) Vikas Garg and Tommi Jaakkola. Predicting Deliberative Outcomes.  ICML (2020).

Ready to apply?

If you want to join our community and start your journey towards Doctoral dissertation submit your application via our electronic recruitment system. The application form will close 6th February 2022 at 23:59 Finnish time (UTC +2).

If you are currently working at Aalto University, please submit your application via HR System Workday (Career – Find jobs – Apply).

Please be prepared to add the following attachments:

  • Cover letter
  • CV
  • Transcript of your Master’s studies

You will be asked to provide also the contact details of 2-3 academic referees.

What we offer?

HICT is a network of world-class professors and researchers with huge passion for their field of study. In HICT you will become part of enthusiastic and professional team of bold and innovative thinkers.

During your Doctoral studies you will be a full-time employee in either Aalto University or the University of Helsinki depending on the supervisor and the research area. You will be covered by occupational health care based on the employment contract.

More information:

General information about the joint HICT call and HICT:

General questions about HICT: Christina Sirviö, HICT team

General questions about recruitment process: Sanni Kirmanen, Aalto University HR

[email protected]

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