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Research Assistant (PhD candidate/PostDoc) - Risk-sensitive choice and reinforcement learning under uncertainty

Technische Universität Berlin offers an open position:

Research Assistant - salary grade E 13 TV-L (PhD candidate/PostDoc)

Risk-sensitive choice and reinforcement learning under uncertainty

Duration: 3 years

Starting Date: April, 1st, 2019

Application deadline: February, 28th, 2019

Faculty IV - Institute of Software Engineering and Theoretical Computer Science / Neural Information Processing

Working field:

The successful candidate is supposed to join a DFG funded project (with Co-PI Dirk Ostwald, Freie Universität Berlin) which combines computational modelling with behavioral and fMRI experiments. The goal is to better understand human decision making and reward-based learning under perceptual uncertainty. The computational framework generalizes the risk-sensitive MDP approach of Yun et al. 2014 (Neural Comput. 26, 1298ff) to a POMDP-based behavioral modelling framework. Planned experiments address response time behavior and neural reinforcement learning processes under perceptual risk. The work program can be biased either towards computational or experimental work depending on the qualifications of the candidate.

Qualifications:

Successfully completed university degree in a subject relevant to the work program; very good programming and English language skills; solid background in decision making and reward-based learning on a theoretical and / or experimental level; experience with computational modelling and the model-based analysis of behavioral and fMRI data is desirable

How to apply:

Please send your application with the usual documents (CV, letter of motivation, transcripts of records, certificates, and the names of two persons who can provide recommendation letters) to Prof. Dr. Klaus Obermayer, FG Neuronale Informationsverarbeitung, Sekr. MAR 5-6, Marchstr. 23, 10587 Berlin or by e-mail to

To guarantee equal opportunities between men and women, applications of women with respective qualifications are explicitly welcome. Severely handicapped persons will be privileged on equal qualification.

Please send copies only. Original documents will not be returned.

 

 

Student Research Assistant (60h/month) – Deep Networks for Modeling Real-world Visual Categorical Decisions in Humans

Technische Universität Berlin offers an open position:

Student Research Assistant (60h/month)

Deep Networks for Modeling Neural Real-world Visual Categorical Decisions in Humans

Duration: 3 years

Starting Date: May 1st, 2019

Application deadline: February 15th, 2019

Faculty IV - Institute of Software Engineering and Theoretical Computer Science / Neural Information Processing

Working field:

The successful candidate will simulate deep networks for visual categorization tasks (including the piloting of alternative deep learning architectures) and evaluate these networks w.r.t. classification performance and the emerging visual representations. These networks will then be used (1) to calibrate visual datasets for experiments with human subjects and (2) to subsequently analyze the visual representations in the human brain recorded by MEG and fMRI.

The position is part of a DFG-funded project together with R. Cichy (FU Berlin).

Qualifications:

Applicants should have very good programming skills, a good command of the English language, competence in machine learning, and a strong interest in working at the interface of machine learning and cognitive neuroscience. Some practical experience with deep learning techniques is a plus.

How to apply:

Please send your application with the usual documents (CV, letter of motivation, transcripts of records, and certificates) to Prof. Dr. Klaus Obermayer, FG Neuronale Informationsverarbeitung, Sekr. MAR 5-6, Marchstr. 23, 10587 Berlin or by e-mail to

To guarantee equal opportunities between men and women, applications of women with respective qualifications are explicitly welcome. Severely handicapped persons will be privileged on equal qualification.

Please send copies only. Original documents will not be returned.

 

 

Please contact Prof. Dr. Klaus Obermayer for information about other possible job openings

Prof. Dr. Klaus Obermayer
Neural Information Processing Group
MAR 5-6, Marchstrasse 23
10587 Berlin, Germany
email: oby(at)ni.tu-berlin.de

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