As part of an external funded project in collaboration with Dan Marcus, Wash. U; Sean Hill, CAMH; and members of the Cogitate Consortium, we are searching for a Scientific Data Engineer to contribute to the development of generic, cross-domain metadata management framework to foster the reuse of open datasets as well as reproducibility of cognitive neuroscience datasets i.e., metadata describing the experimental context of studies employing fMRI, MEEG, and ECoG. The successful candidate will also heavily contribute to the development of data infrastructure including storage, streaming and analysis tools for reproducible science based on the BIDS standard. Efforts will be devoted to develop tools for an efficient organization and exploration of raw and processed datasets. The position is ideal for networking in the open science community as it includes interaction with the open (neuro)science community; and is a unique opportunity for someone keen to contribute to the development of open-science and large-scale collaborations and aiming to contribute to community efforts and dissemination.

Your tasks in interdisciplinary research projects focus on:
• Review of existing approaches and tools, Requirement specification, Conceptual design, blueprint of implementation, Proof-of-concept application to Cognitive Neuroscience
• Presentation and publication of the results
• Exchange and networking within national (NFDI, MPDL) and international (RDA, EOSC) initiatives
• Developing, testing and implementing scientific software i.e., standardized neuroscience data acquisition, reproducible analysis pipelines and data storage for open science building on the BIDS standard
• Providing training and support for students and postdocs at varied levels of competence in modern, high quality, open science/source coding practices
• Providing support and training for data management
• Being the lab’s interface with the Institute’s core IT team