Doctoral researcher, Project: 'Algorithms vs humans: physical problem solving'

(salary grade E13 TV-L, under the reserve that funds are granted, starting not later than from 1.10.2021 / for 3 years / closing date for applications 20.11.2020, Ref SCIoI-C3-30a)

The Technische Universität Berlin invites applications for a Phd position for the Cluster of Excellence “Science of Intelligence”.

What are the principles of intelligence, shared by all forms of intelligence, no matter whether artificial or biological, whether robot, computer program, human, or animal? And how can we apply these principles to create intelligent technology?

Answering these questions – in an ethically responsible way – is the central scientific objective of the new Cluster of Excellence Science of Intelligence (, where researchers from a large number of analytic and synthetic disciplines – artificial intelligence, machine learning, control, robotics, computer vision, behavioural biology, psychology, educational science, neuroscience, and philosophy – join forces to create a multi-disciplinary research program across universities and research institutes in Berlin. Inter

disciplinary research projects have been defined (, which combine analytic and synthetic research and which address key aspects of individual, social, and collective intelligence.

Working field

“Analyzing human physical reasoning and strategy exploration on physical puzzles”

This project investigates human physical problem solving on virtual physical puzzles. The goal is to understand what strategies humans develop and use to solve such tasks. We will design novel experimental scenarios to perform empirical studies with humans, but will use the same scenarios to also evaluate computational methods for physical problem solving. In particular, we build on recent methods for physical reasoning and robot manipulation planning. Key empirical questions concern the repertoire of strategies employed by humans and whether we find certain kinds of strategy switching. A key question on the computational side is whether their internal strategies to explore potential solutions can be related to human behavior.



Doctoral project “Algorithms vs humans: physical problem solving”

A core focus of the doctoral project is to develop and apply computational solvers for physical reasoning on the virtual physical puzzles. Based on this, the student will analyse the behavior of these solvers on the puzzles for patterns analogous to those we analyze in the human data. On the technical side, the project will build on existing optimization-based solvers for physical reasoning. These have been shown successful in 3D physical manipulation planning, but the virtual physical puzzle will still raise challenges for the existing solvers and will require to extend them. Further, an important aspect not covered by existing solvers is how to deal with experienced failure. The doctoral project will investigate in Bayesian exploration methods (BayesOpt) to tune continuous parameters of fixed skeletons to enable solving, as well as strategies to switch to alternative skeletons.

The resulting methods are to produce data analogous to the human experiments. Based on this data, new puzzles are designed which are predicted to be particularly hard or easy.

All positions require participation in research colloquia, lecture series and workshops, as well as an active engagement in the Cluster’s research activities.



Applicants must hold a Diploma/Master’s degree in computer science or a related discipline and should have proven skills/background in following topics:

  • Interest in interdisciplinary research in the context of the Center of Excellence “Science of Intelligence”
  • AI planning or robotic manipulation planning
  • Strong analytical skills (linear algebra, calculus, AI theory)
  • Strong programming skills (preferably in C++, or Python)

Application procedure

Candidates should upload their application preferably via the portal in order to receive full consideration.

Applications should include: motivation letter, curriculum vitae, transcripts of records (for both BSc and MSc), copies of degree certificates (BSc, MSc), abstracts of Bachelor- and Master-thesis, list of publications and one selected manuscript (if applicable), two names of qualified persons who are willing to provide references, and any documents candidates feel may help us assess their competence.