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<p><i>Please circulate - apologies for cross-posting.</i></p>
<p>The <a moz-do-not-send="true" href="bachlab.org">Hertz Chair for
Artificial Intelligence and Neuroscience</a> at <a
moz-do-not-send="true" href="www.uni-bonn.de/en">University of
Bonn</a> 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).<br>
<br>
The aim of the research is to understand the <b>cognitive
neurobiology of human threat avoidance</b>, 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). <br>
<br>
The successful candidates will be based at the <b>University of
Bonn, Campus Endenich</b>, 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. <br>
<br>
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 <a class="moz-txt-link-abbreviated
moz-txt-link-freetext" href="mailto:d.bach@uni-bonn.de">d.bach@uni-bonn.de</a>.<br>
<br>
<b>Post doc positions are initially based in the following fields.
We welcome enquries from candidates in related fields of
cognitive-computational neuroscience.</b><br>
<b><br>
</b><b>Post doc Motion Capture</b><br>
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. <br>
<br>
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.<br>
<br>
<b>Post doc VR</b><br>
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. <br>
<br>
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.<br>
<br>
<b>Post doc learning theory</b><br>
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. <br>
</p>
<p> 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.</p>
<p><b>Post doc software development</b><br>
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. <br>
</p>
<p>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.<br>
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