Data Support Associate
camh
Through its core values of Courage Respect and Excellence CAMH is implementing its Strategic Plan: Connected CAMH to transform lives ignite innovation and discovery revolutionize education and drive social change. CAMH is more than a hospital it is a cause. They aim to eliminate prejudice and discrimination and shape a world where mental illness is central to our healthcare system a world where Mental Health is Health.
To learn more about CAMH please visit their website at: .
The Geriatric Mental Health Research Services (GMHRS) at the Centre for Addiction and Mental Health (CAMH) is seeking a casual Scientific Associate to provide computational support (with a focus on ML Signal Processing Entropy) in the analysis of biomarkers data in particular EEG data.
The candidate will report to the Research Operations Manager of GMHRS. The position will require the individual to apply advanced programming skills (in R/Python) to process and analyze large datasets while working collaboratively with interdisciplinary teams. The successful candidate will be expected to assist with study start-up (e.g. supporting ethics submissions writing study protocols) work closely with GMHRS personnel to compile sensitive participant data analyze data co-supervise students and junior staff produce manuscripts and assist with grant writing. The candidate will support a workplace that embraces diversity encourages teamwork and complies with all applicable regulatory and legislative requirements. The successful candidate must have a PhD in Psychology/Biostatistics Computer Science or in a relevant field
A minimum of at least one(1) years relevant research experience
Extensive experience analyzing EEG data with preference given to candidates who have employed methods in EEG analyses
Demonstrated familiarity with analysis tools and methods
Advance programming skills in R/Python with demonstrated familiarity with other analysis tools and methods
A proven track record and aptitude in scientific publishing
The candidate is expected to have previously carried out and published research related to EEG and signal processing with evidence of publication in high-impact journals
Ability to collaborate effectively with colleagues and the scientific community
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