Scientific Associate - Brain Health Imaging Centre

at  Centre for Addiction and Mental Health

Job Description
As Canada’s largest mental health care provider, the Centre for Addiction and Mental Health (CAMH) provides evidence to drive system and policy change through the implementation of innovations and novel service delivery interventions. The Brain Health Imaging Centre (BHIC) is one of the primary research areas of CAMH and focuses on new brain imaging tools and methods used in mental health and addictions for clinical neuroscience research.

POSITION DESCRIPTION:

The BHIC is seeking a Scientific Associate with expertise in medical physics and image quantification pertaining to positron emission tomography (PET). The successful candidate will be responsible for calibration and quality maintenance of the two clinical PET scanners (currently an HRRT and GE Discovery MI PET/CT), and two hybrid preclinical PET scanners (Mediso PET/MR and PET/CT) in the Centre, as well as the associated auxiliary equipment (dose calibrators, automated blood sampling systems, radiometabolite laboratories, gamma-counters, etc.). They will also assist with supporting the computer and network infrastructure used to securely manage, process, transfer and store the PET and MRI data generated at the Centre. This position is located on-site at 250 College Street, and the candidate will report to the Staff Scientist (PET Physics) at the CAMH BHIC.

Job Requirements

• Applicants must possess a PhD in a discipline relevant to PET physics and/or medical physics.
• Applicants must possess 1-2 years relevant experience with quantitative modelling and medical imaging.
• Experience with quality maintenance of lab equipment, and/or engineering physics are considered favourably. Any additional knowledge and expertise of PET tomographs, dual modality PET/MR, PET/CT or preclinical imaging will be considered an asset.
• The ideal candidate will have a working understanding of PET methods including system setup, calibrations and the necessary corrections required to generate quantitative data. Experience in processing PET image data, including image reconstruction and registration / motion correction is an asset.
• Experience with scripting and software development, (MATLAB, python, or another appropriate language) to address the requirements of the program at the BHIC, and a knowledge of imaging data structures (e.g. NIFTI, DICOM, ecat, BIDS, etc.) will be considered favourably.
• Experience with network monitoring software (i.e., Nagios) and with other systems administration related tasks will be viewed favourably.
• Experience in developing analytical pipelines including generation of input functions, radiometabolite analysis, and software packages including PMOD, VivoQuant, Amide, NumPy, FSL etc., or neuroinformatics platforms (i.e. XNAT), is a benefit, along with a proven expertise relevant to brain-PET imaging studies.
• Expertise in quantitative modelling, including kinetic modelling, regional analysis and parametric mapping is also an asset.
• The ability to develop appropriate solutions to overcome challenges associated with discovery and for processing pipelines for novel PET tracers for neuroimaging is essential.
• Additional skills will include knowledge of Quality Assurance/Quality Control methods for PET data and experience handling and performing experiments with radioactive materials. Nuclear Energy Worker (NEW) status is mandatory and must be sought upon employment at the Centre if not already obtained.
• Excellent written and communication skills are essential. The candidate must be willing to provide flexibility and the ability to adapt to a fast-paced research environment, as well as to work independently, in a highly collaborative working environment

The candidate will be responsible for helping to develop and implement PET methodology to overcome challenges to image quantification, particularly those associated with newer PET scanners. They will acquire data and perform image processing for physical characterization tests of PET systems (i.e. NEMA), dosimetry, quality control and calibration. They will perform analysis of human PET and MRI image data, help develop image analysis pipelines and provide basic training to help establish methodology for new PET tracers amongst CAMH researchers and their trainees, and assist with the preparation of this data for publication.
As part of their core responsibilities, they will implement methods to enter and organize the data into standard data structures used in research (such as the Brain Imaging Data Structure [BIDS]). They will help set up and maintain shared computing and software resources for authorized users within BHIC, and have data management responsibilities including data backup and oversight of data storage. The candidate will interact and liaise with the CAMH Research IT and the Krembil Centre for Neuroinformatics teams to establish communication with their servers and data services as appropriate.
The successful candidate will work in close collaboration with the Methodology Team including Staff Scientists (PET Physicists and Modellers), other Scientific Associates, and their trainees to maintain integrity of all PET and associated data and integrate the PET data into subsequent analysis, and they will help develop and enable data quality control pipelines to satisfy regulatory requirements for clinical studies. They will perform investigations to help validate new knowledge, imaging and analysis and methods in imaging sciences. The candidate will provide training to CAMH staff and trainees and will also be involved in preparing standard operating procedures and related documentation. Other research-related administrative duties will also be required.
The candidate will support a workplace that embraces diversity, encourages teamwork and complies with all applicable regulatory and legislative requirements. This position is located at 250 College Street.

Job Requirements

• Applicants must possess a PhD in a discipline relevant to PET physics and/or medical physics.
• Applicants must possess 1-2 years relevant experience with quantitative modelling and medical imaging.
• Experience with quality maintenance of lab equipment, and/or engineering physics are considered favourably. Any additional knowledge and expertise of PET tomographs, dual modality PET/MR, PET/CT or preclinical imaging will be considered an asset.
• The ideal candidate will have a working understanding of PET methods including system setup, calibrations and the necessary corrections required to generate quantitative data. Experience in processing PET image data, including image reconstruction and registration / motion correction is an asset.
• Experience with scripting and software development, (MATLAB, python, or another appropriate language) to address the requirements of the program at the BHIC, and a knowledge of imaging data structures (e.g. NIFTI, DICOM, ecat, BIDS, etc.) will be considered favourably.
• Experience with network monitoring software (i.e., Nagios) and with other systems administration related tasks will be viewed favourably.
• Experience in developing analytical pipelines including generation of input functions, radiometabolite analysis, and software packages including PMOD, VivoQuant, Amide, NumPy, FSL etc., or neuroinformatics platforms (i.e. XNAT), is a benefit, along with a proven expertise relevant to brain-PET imaging studies.
• Expertise in quantitative modelling, including kinetic modelling, regional analysis and parametric mapping is also an asset.
• The ability to develop appropriate solutions to overcome challenges associated with discovery and for processing pipelines for novel PET tracers for neuroimaging is essential.
• Additional skills will include knowledge of Quality Assurance/Quality Control methods for PET data and experience handling and performing experiments with radioactive materials. Nuclear Energy Worker (NEW) status is mandatory and must be sought upon employment at the Centre if not already obtained.
• Excellent written and communication skills are essential. The candidate must be willing to provide flexibility and the ability to adapt to a fast-paced research environment, as well as to work independently, in a highly collaborative working environment.