Connectionists: Post doc positions in AI and Neuroscience at University of Bonn, Germany (topics: motion capture, virtual reality, learning theory, ML and software development)

[Dominik Bach]

/Please circulate - apologies for cross-posting./

The Hertz Chair for Artificial Intelligence and Neuroscience 
<https://eur01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fbachlab.org%2F&data=04%7C01%7Cd.bach%40ucl.ac.uk%7Ce83c930304a54adb98d908d9e727f7ef%7C1faf88fea9984c5b93c9210a11d9a5c2%7C0%7C0%7C637794982333088555%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=%2BrCR4cDmuKU0oFVqdU%2BOt16nnUmMK1zEtgggP3gzni4%3D&reserved=0> 
at University of Bonn 
<https://eur01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.uni-bonn.de%2Fen&data=04%7C01%7Cd.bach%40ucl.ac.uk%7Ce83c930304a54adb98d908d9e727f7ef%7C1faf88fea9984c5b93c9210a11d9a5c2%7C0%7C0%7C637794982333088555%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=9Wg6KjJvxg9NS2Bp8beV0LbhMvqf2mnR%2FSfrP%2Fdaon4%3D&reserved=0> 
is looking to recruit postdoctoral fellows for an interdisciplinary 
neuroscience research program coordinated and supervised by Professor 
Dominik Bach. This program brings together researchers with expertise in 
cognitive(-computational) science, movement science, machine-learning, 
and software development. This provides an exciting opportunity for 
postdoctoral candidates to work at the cutting edge of human cognitive 
science and neuroscience research. Collaboration partners in this 
endeavour are based at Max-Planck-Institute for Biological Cybernetics 
in Tübingen (Germany), University of Tübingen (Germany), Max-Planck UCL 
Centre for Computational Psychiatry (UK) and Wellcome Centre for Human 
Neuroimaging (UK).

The aim of the research is to understand the *cognitive neurobiology of 
human threat avoidance*, in terms of acute escape behaviour as well as 
medium- and long-term threat forecasting. Our research strongly builds 
on computational modelling of behaviour and neural systems, theories of 
artificial agents, machine-learning methods such as pose estimation and 
motion sequencing, and research automation by software design and by 
self-learning data analysis methods. Our team culture is collaborative, 
agile, and shaped by technical sophistication. We believe in open, 
reproducible, and sustainable precision science. We host a 
state-of-the-art virtual reality and motion capture lab, and have access 
to human neuroimaging facilities (3 T and 7 T MRI, OPM-MEG).

The successful candidates will be based at the *University of Bonn, 
Campus Endenich*, in direct vicinity to natural and computer science 
departments and other interdisciplinary Hertz Chairs. The University of 
Bonn is an internationally leading research university, providing an 
intellectually stimulating environment. At University of Bonn, 
postdoctoral salaries start at around 55'000 €/year depending on prior 
post-doctoral experience. The positions are available on or after 1 
April 2022. An initial appointment for a two-year period will be made 
with potential for extension depending on successful performance of 
research and publications. University of Bonn is committed to diversity 
and encourages applications from underrepresented groups.

Qualified postdoctoral applicants should submit a current CV including 
publication list, a personal statement describing their experience and 
interests, and contact information for three references to 
d.bach at uni-bonn.de.

*Post doc positions are initially based in the following fields. We 
welcome enquries from candidates in related fields of 
cognitive-computational neuroscience.*
*
**Post doc Motion Capture*
The goal is to understand human motor behaviour under acute, immediate 
threat. We investigate this in an immersive virtual reality (VR) 
environment, in which people can move to avoid various threats. The 
candidate will conduct full-body markerless and marker-based motion 
capture, pose estimation, recover kinematics, and structure the recorded 
movement trajectories with statistical and machine-learning models.

Applicants should have (or be close to obtaining) a PhD in 
machine-learning, robotics, computer science, motor science, 
biomechanics, computational neuroscience, or a related area, by the 
agreed start date of the position. Experience with motion capture, pose 
estimation, inverse kinematics (in humans or robots), movement 
trajectory analysis and structuring/sequencing are essential. Strong 
background in contemporary machine-learning and applied statistics is 
essential, as are solid mathematical skills and good general IT and 
software development knowledge. Familiarity with virtual reality and/or 
human/animal defensive behaviour would be desirable.

*Post doc VR*
The goal is to develop a cognitive-computational understanding of human 
decision-making under acute, immediate threat. We investigate this in an 
immersive virtual reality (VR) environment, in which people can move to 
avoid various threats. The candidate's role will be to maintain and 
advance an existing Unity-based research platform, build specific 
suitable scenarios, conduct experimental studies with this setup, and 
analyse the data.

Applicants should have (or be close to obtaining) a PhD in 
cognitive-computational (neuro)science, applied machine-learning, 
biomechanics, motor science, a quantitative field of psychology (e.g. 
decision-making, perception), or a related area by the agreed start date 
of the position. Experience with Unity and C# are essential, familiarity 
with R would be desirable. The successful candidate will have experience 
in programming is essential, solid knowledge of decision science, 
applied statistics and a good publication record.

*Post doc learning theory*
The goal is to understand the computational algorithms by which humans 
learn to predict and avoid threat. Experimentally, we investigate this 
using human fear conditioning and VR-based avoidance learning. The 
candidate will build and test computational learning models using 
existing experimental data, and design new experiments to disambiguate 
candidate models. They will maintain and advance software frameworks for 
model benchmarking and Bayesian experimental design optimisation, and 
model-based data analysis.

Applicants should have (or be close to obtaining) a PhD in 
cognitive-computational (neuro)science, computer science, machine 
learning, mathematics, a quantitative field of psychology (e.g. 
decision-making, perception), or a related area by the agreed start date 
of the position. Experience with learning theory in biological or 
artificial agents is essential; familiarity with analysis of 
biological/psychological data would be desirable. The successful 
candidate will have solid knowledge of mathematical statistics and 
experience with modern software development techniques.

*Post doc software development*
Our goal is to develop open, reproducible and sustainable, precision 
methods in the field of human cognitive neuroscience. To this end, we 
develop and maintain several software frameworks for computational model 
benchmarking, model-based data analysis, Bayesian experimental design 
optimisation, and collaborative data bases. The candidate will build on 
contemporary methods theory and metrology to advance and integrate these 
tools into an autonomous, continuously integrating, and self-learning 
software ecosystem.

Applicants should have (or be close to obtaining) a PhD in computer 
science, cognitive-computational (neuro)science, software engineering, 
machine learning, mathematics, a quantitative field of psychology (e.g. 
decision-making, perception), or a related area by the agreed start date 
of the position. Experience with modern software development techniques 
is essential. A good understanding of cognitive-computational modelling 
and data sharing practices would be desirable. The successful candidate 
will have solid knowledge of applied statistics and machine learning, 
and experience with managing biological/psychological data.
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