PhD Position in Computational Neuroscience at TU Dresden, CMC Lab

Dresden           ·           Part time

At the Department of Child and Adolescent Psychiatry in the Faculty of Medicine (TU Dresden) and within the Research Unit “Cognitive Neurophysiology” (Prof. Beste), the newly established “Computational Machinery of Cognition (CMC)” lab (Prof. Safavi) offers a

PhD position (m/f/x) 

in part time (65%), initially limited to 36 months. Remuneration is in accordance with the collective agreement for the public service of the Länder (TV-L / E13).

The overarching research theme of the CMC Lab is understanding the computational machinery that supports our cognitive processes. Cognition spans a wide range of functions (from perception to action and planning), and it is one of the most remarkable capabilities of the brain. In this lab, we want to understand the computations (in particular, inference, and decision processes) that support our cognition and the biophysical machinery that implements these computations. In the CMC lab, we will do normative and biophysical modeling of cognitive functions; we will test these models with neural and behavioral data (in collaboration with experimental labs); and we will develop methods for multi- and cross-scale analysis of neural data to better capture the neural markers of these cognitive process. The Department values the culture of collaboration, thus we extensively collaborate with labs in Dresden and other labs nationally and internationally (e.g., MPI for Biological Cybernetics and Intelligent Systems).

The project will focus on the computational principles of “Neural events”. Neural events are characteristic, transient, and coordinated neural activities that we can identify in aggregated signals (e.g., local field potentials or LFPs). Some neural events have signatures across several scales (neurons, neural populations, and large-scale networks). Moreover, they are also closely connected to behavior; for instance, Sharp-Wave Ripples are broadly involved in cognitive functions (from memory consolidation to offline and online planning). The key gaps that the position holder will work on include: How can we detect neural events in data reliably? We will develop unsupervised machine-learning methods to identify neural events. If and how neural events are coupled to behavior? We will use our method(s) to investigate the occurrence of different kinds of neural events in a variety of behavioral tasks. How do rich multi-scale dynamics of neural events support the behavior? We will characterize the multi-scale signature of neural events (e.g., how different brain regions interact/communicate in the vicinity of each event) during a variety of behavioral tasks. Overall, in this project, we will find accessible neural markers of cognitive processes, that likely shed light on behaviorally relevant coordination mechanisms in the brain.

We expect (N=necessary, D=desired, P=plus):

• (N) Have background (Master / Diploma) in computational neuroscience, neuroscience, physics, mathematics, statistics, machine learning, psychology and other related fields.
• (N) Being comfortable with programming (best would be, Python, or/and Matlab).
• (N) Excellent communication skills in English.
• (N) Willingness to work responsibly and within part of a team.
• (D) Have experience in the analysis of neurophysiology data.
• (D) Have experience with computational and systems neuroscience.
• (D) Familiarity with machine learning techniques or / and having a technical background (physics, mathematics, engendering, etc.).
• (P) Basic knowledge of software engineering (e.g., packaging scientific tools).

We offer:

• Activity in leading medical and cognitive neuroscience research.
• Possibility to implement own ideas and work in an innovative interdisciplinary team in research and teaching.
• Work in a highly international and multi-disciplinary team.
• Long-term career development opportunities.
• Reconciling flexible working hours and home office to make the combination of family and career a reality.
• Care of your children through partnerships with children’s institutions near the University Hospital.
• Use of company prevention offers, courses, and fitness in our Carus Vital health centre.
• Job-oriented further and advanced training with individual planning of your professional career.

Application of women is appreciated. Disabled persons with equal qualifications will be preferred.

We kindly ask you to apply preferably via our online form to make the selection process faster and more effective. Of course, we also consider your written application without any disadvantages. Please submit your application (preferably) with the following form by November 30th 2023 with registration number KJP0923041. Please include the following documents: a cover letter, brief research interests, and your CV. For further information please contact Shervin Safavi by E-Mail: shervin.safavi@uniklinikum-dresden.de

Please click here to apply.