Student Research Assistant (41h) in the Metamotor Lab

Student Research Assistant (41 h / month)

Field: Metacognition of action

To be filled: Feb, 2019

Application due: Feb 11, 2019

Reference Key: 2113/40/18

 

Working field:
We are looking for one research assistant (SHK) to work in Metacognition of action with is un the Metamotorlab (http://metamotorlab.filevich.com). We are a small team studying how (much) we know about the way we move our bodies.
The position is for 41 hours/month and will include literature search, programming experimental tasks (in Matlab, JavaScript), collecting and analysing behavioural and neuroimaging data (in Matlab, R).

Requirements:

Relevant study background; Good English; Good Microsoft Office knowledge; Experience with programming; Ability to work in a team; Knowledge of Signal Detection Theory is a plus.

How to apply:

Interested candidates, please contact Elisa Filevich via email
(elisa.filevich [at] bccn-berlin.de). Full applications in English (including a letter of motivation and CV) should be sent before February 11, 2019 with reference key 2113/40/18 to the contact address given above

 

 

Student Research Assistant (60h) in the Obermayer Lab

Student Research Assistant (60 h / month)

Field: Deep networks for modelling real-world visual categorical decisions in humans

To be filled: May 1, 2019

Application due: Feb 15, 2019
Reference number:
Applications received after this date may still be considered.

 

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).

Requirements:
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) preferably by e-mail (klaus.obermayer@tu-berlin.de).