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PhD Position in Computational Neuroscience (f/m/d) funded position for 3 years
Background: The human brain consists of 86 × 10& neurons, whereas the zebrafish larval
brain only contains approximately 10'. Despite its smaller size, the basic neuronal architecture
or bauplan of the zebrafish brain is largely comparable to its human counterpart. Moreover,
not only are the basic building blocks and neural circuitry evolutionary conserved, but in
addition larval zebrafish are small and transparent, thereby offering a unique opportunity to
observe neuronal activity with high resolution microscopy. Indeed, the zebrafish was the first
vertebrate organism in which neuronal activity throughout the whole brain has been recorded
in real time (Ahrens et al., 2013). Although we can now literally see a fish thinking, the obtained
data sets are large and require computational methods to gain fundamental insights into the
activity patterns of neural networks and their mutual interplay (Haesemeyer et al., 2019).
Project: We are looking for an enthusiastic PhD student to analyze, model, and possibly
predict neural activity. In the PhD project, the candidate will analyze activity patterns of nerve
cells throughout the entire brain obtained by advanced imaging techniques such as light sheet
microscopy. This requires, first, the identification and segmentation of signals and their 3Dreconstruction
over time, and, second, the registration of individual brains and their
corresponding activity patterns onto a reference brain in order to compare different data sets.
To this end, you will develop deep learning approaches within a Python framework. Since the
imaging datasets are usually large (in the terabyte range), GPU-based methods to accelerate
data processing routines will be implemented together with existing frameworks such as
advanced normalization tools (ANTs). In addition, the candidate should be interested in
working in an interdisciplinary and cutting-edge research area together with engineers,
biologists, and data scientists.
The goal of the PhD project is to analyze and quantify neuronal activity patterns across the
entire brain in response to externally provided stimuli mapped onto a reference brain. This will
provide fundamental insights into brain function in health and disease and may ultimately also
lead to novel and better treatments of neuropsychiatric disorders such as depression, anxiety,
and drug addiction.
You should have a very good knowledge in coding (in particular Python) and computation in
general. Ideally, you already have experience in the implementation of deep learning
techniques and the simulation and modeling of neuronal networks. Prior knowledge in biology
or microscopy is not necessary, but a keen interest in neuroscience is encouraged. You will
work in an international team together with neurobiologists and microfluidic engineers; thus
solid conversation skills in English is required.
The PhD position is offered in the Köster Lab at the Zoological Institute (https://www.tubraunschweig.
de/en/zoology) in Braunschweig, Germany. The preferred starting date is the
01.07.2021, and the duration is 3 years. The position is part-time suitable, but should be
occupied 100% and is aimed to lead to a PhD degree as Dr. rer. nat. at the Life Sciences
Faculty of the Technical University (TU) of Braunschweig.
The payment is made according to task assignment and fulfillment of personal requirements
to salary group EG 13 TV-L, 65% (approximately: 2.000 €/month net). Applicants from non-EU
countries may have to successfully complete a visa process before hiring can take place and
are welcomed to apply.
The TU Braunschweig aims to increase the share of women in academic positions.
Applications from female candidates are very welcome. Where candidates have equal
qualifications, preference will be given to female applicants. Candidates with handicaps will be
preferred if equally qualified. Please enclose a proof when applying for the position.
Applications: should be sent by e-mail to Reinhard Köster (r.koester@tu-bs.de), and must
contain the following documents.
• Motivation Letter including contact information for two references
• Curriculum Vitae including complete address, phone number, email address,
educational background, language skills, and work experience
• copies of bachelor and master degrees and transcript of grades in original language
and in English or German translation
• additional documents should be provided on request
All documents should be in the PDF format; preferably, please provide the entire application
in a single file. Personal data and documents relating to the application process will be stored
electronically. Please note that application costs cannot be refunded.
Deadline forapplications: until position is filled.
For any questions, please contact: Dr. Jakob von Trotha or Prof. Reinhard Köster
Email: j.von-trotha@tu-braunschweig.de, r.koester@tu-bs.de