Postdoctoral position for the development of large-scale electrophysiological data management infrastructure

2-year position: $62,500/year plus benefits (~ total $75,000/year)

This salary is guaranteed by a partnership between the Department of Neurosciences (https://neurosciences.umontreal.ca), the Faculty of Medicine of the Université de Montréal (https://medecine.umontreal.ca) and IVADO (https://ivado.ca), an interdisciplinary, cross-sectoral research, training and knowledge mobilization consortium whose mission is to develop and promote a robust, reasoning and responsible AI.

Requirements: The applicant should hold a PhD (e.g. electrical or biomedical engineering, neurosciences, or complementary field) and have research expertise in system neuroscience, programming, and data processing and analyses.

Major advances in electrophysiological recording technologies have led to an explosion in the size of datasets, as well as new challenges in processing and managing them. In particular, the advent of wireless large-scale neurophysiology and deep-learning-based pose estimation enables us to study new scientific questions on complex, unconstrained behaviors. As the pace at which we acquire data has accelerated exponentially in recent years, there is an urgent need for efficient automated pipelines to process raw data from labs into analysis-ready datasets. To address these challenges, several research groups at the department of neuroscience (P. Cisek, N. Dancause, B. Ebitz, A. Green, M. Perich) aim to develop and deploy automated approaches to process signals recorded in our labs into analysis-ready datasets; 2) create a unified data storage and management framework to facilitate data sharing and collaborative, neuro-AI, analyses. These goals are closely aligned with those of the Union Neuroscience et Intelligence artificielle Quebec (UNIQUE; https://www.unique.quebec) center, the strategic research cluster of the Fonds de Recherche du Quebec – Nature et Technologie (FRQ-NT), IVADO and the Quebec Artificial Intelligence Institute (Mila; https://mila.quebec).

The main objective of the present position is to develop and deploy automated approaches to process signals from the labs into analysis-ready datasets. The postdoctoral trainee will design and develop automated processing pipelines, from raw data collected in the labs to analysis-ready state, for each type of data collected. The pipeline must adapt and enhance our current tools implemented in Matlab, R or Python. This includes incorporating automated spike sorting tools such as MountainSort, KiloSort, and Full Binary Pursuit, handling local field potential signals with software like Chronux and FieldTrip, as well as creating user interfaces. The postdoctoral trainee will be responsible for creating Standard Operating Procedures and lead user training.   

This position is a great opportunity for a postdoctoral trainee seeking training at the intersection of academia and industry. The candidate should have adequate training in disciplines such as engineering, data sciences, machine-learning or neurosciences. The postdoctoral trainee will advance cutting-edge platforms for large-scale behavioral and neurophysiology experiments shared by several research groups on campus at the Université de Montréal. They will participate in the advancement of open source in neuroscience. The position will include working with unique electrophysiological datasets that from ongoing scientific projects of one or more of the participating research labs. These data will provide opportunities to develop novel or high-dimensional analytical tools that could lead to authorship on additional publications.            

For application: Please send a short cover letter, resume and the names of 3 references to:

Numa Dancause, BSc(PT), PhD

Professor, Associate Director                                                 

Département de Neurosciences                                            

Université de Montréal

Email:  marlene.boutet@umontreal.ca

Paul Cisek, PhD

Département de neurosciences

Université de Montréal

Physical: 2960 chemin de la tour, local 4117

Montréal, QC H3T 1J4 CANADA

Mailing: CP 6128 Succursale centre-ville,

Montréal, QC H3C 3J7 CANADA

e-mail: paul.cisek@umontreal.ca

Web: www.cisek.org/pavel