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MLOps Research Placement or Practicum Student
The Augmented Intelligence and Digital Tech for Mental Health Group (AID4MH) (www.aid4mental.health), based at the Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health, Toronto is seeking a research placement student for developing Machine Learning Operations (MLOps) framework for enabling digital mental health research and operations.

TThe student will assist with projects designing end-to-end ML production system pipelines addressing project scoping, data needs, modeling strategies, and deployment requirements, with a main focus on the following components:
- Data lifecycle: Collection, labeling, and storage.
- ML modeling pipelines in production: neural architecture search, model resource management, high-performance modeling, model analysis, and interpretability.
- ML model deployment in production: model serving patterns and infrastructures, model management and delivery, and model monitoring and logging.
The analytical workflows will be geared towards understanding the individualized real-world experience of mental health using multimodal data (e.g. electronic medical records, sensor-based data from wearables and smartphones, etc).

This position is currently located at 250 College Street Site, Toronto with remote work as an option.

The primary responsibilities of this position will involve:
- Building data pipelines for ingestion, quality assessment, and processing
- Creating containerized images for ML/AI pipeline functions and associated dependencies
- Performing container orchestration using available data/computing clusters
- Implementing tools and techniques to effectively manage modeling resources and serve offline and online inference requests
- Implementing Continuous Integration and Continuous Delivery (CI/CD) workflow automation
- Maintaining high-quality online documentation for computational tools and analysis workflows
Qualifications:
- Enrolled at University/College in a Bachelors/Masters degree-granting program (e.g. Computer Science, Software Engineering, Bioinformatics, Machine Learning)
- Completed at least one year of CS/IT/MLoPS related coursework
- Demonstrable experience writing open-source computational scripts for ML pipelines, container DockerFiles, and YAML deployment configuration files
- Experience in using one or more of the open-source MLoPS frameworks:
Evidence working collaboratively in a team setting is an asset. Evidence of strong written and oral communication skills and working collaboratively in a team setting are strong assets. The person will also have an active interest in mental health and a passion for findable, accessible, interoperable, and reusable (FAIR) data solutions in biomedical research. They will also support a workplace that embraces diversity, encourages teamwork, and complies with all applicable regulatory and legislative requirements.
About Krembil Centre For Neuroinformatics (KCNI):
The Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health (CAMH) is harnessing the power of high-performance computing to integrate and analyze the wealth of data generated about the brain. Our research is performed in an open science environment, with an emphasis on reproducible data-driven research and a patient-centric approach to accelerate the identification and treatment of mental illness. A focus on global collaboration is key to transforming our understanding of mental health and its treatment. The center operates as an incubator for medical technologies to identify, manage and treat mental illness while shaping policy at national and global levels.

Candidates require the ability to work effectively with individuals from diverse backgrounds. Bilingualism (French/English) and/or proficiency in a second language are an asset.

Vaccines (COVID-19 and others) are a requirement of the job unless you have an exemption on a medical ground pursuant to the Ontario Human Rights Code.

CAMH is a Tobacco-Free Organization.

CAMH is fully affiliated with the University of Toronto and is a teaching hospital and research institute. As a CAMH employee, you will be expected to actively support CAMH’s teaching and research activities, in addition to supporting the clinical work of the hospital.As an employment equity employer, CAMH actively seeks Aboriginal peoples, visible minorities, women, people with disabilities, (including people who have experienced mental health and substance use challenges), and additional diverse identities for our workforce.
Applied NLP Postdoctoral Fellow – Mental Health
The successful candidate will co-lead various NLP-related projects at KCNI and AID4MH group. The work will focus on applying state-of-the-art NLP methods to learn about individuals’ lives, histories, clinical characteristics, and experiences from real-world data. The data will include but not be limited to multimodal and longitudinal electronic health records, psychiatric notes, psychotherapy transcripts, personalized social media data streams, etc.

What you will do:
- Lead the development of reusable and reproducible NLP pipelines for extracting key psychological features from unstructured data (e.g., electronic health records, psychotherapeutic texts, social media data streams)
- Conduct statistical analysis using NLP features derived from clinical texts to predict mental health outcomes (e.g., treatment response, risk of suicide, inpatient violence) as well as patient phenotyping
- Collaborate with an interdisciplinary team of scientists and clinicians to evaluate potential sources of biases in unstructured data
- Support an NIMH-funded project aimed at learning proximal risk factors of suicide based on real-world data streams
Qualitifcations:
- Ph.D. in Computer Science, biomedical informatics, or related field
- Proven expertise in NLP/language modeling demonstrated by strong publication record in NLP, ML, or related areas (including blogs, tutorials, etc.)
- Fluent in Python programming and code management (Git)
- Experience in using one or more open-source NLP frameworks (TensorFlow, PyTorch, Caffe2, Spacy, Keras, BERT and Transformer-based models, etc)
- Deploying NLP models on cloud infrastructure
- Strong communication, teamwork, and leadership skills
- Ability to work independently and lead projects collaborating with interdisciplinary teams such as clinicians, nurses, medical anthropologists, bioethicists, etc.
- Experience in working with healthcare data and/or mental health outcomes is an asset, but not a requirement for this position
How to Apply:
- Online through Indeed or LinkedIn
- Alternatively email your CV, top 1-3 papers (or other scientific writings), and a brief one-page statement of research interests that highlights your past work and future goals to marta.maslej {at} camh.ca with subject line:
Start Date: ASAP
Term: Initially 1 year subject to renewal based on performance and continued funding

About The Centre for Addiction and Mental Health (CAMH):
The Centre for Addiction and Mental Health (CAMH) is Canada’s largest mental health teaching hospital and one of the world’s leading research centers in its field. CAMH is fully affiliated with the University of Toronto and is a Pan American Health Organization/World Health Organization Collaborating Centre. CAMH has one of the largest mental health and addiction patient bases in the world, providing care to more than 34,000 unique patients annually, and is one of the largest training facilities in the world for psychiatrists, allied mental health professionals, and researchers. CAMH’s world-class research facilities enable over 200 scientists, more than 600 research staff, and over 400 trainees to conduct groundbreaking research in the areas of brain science, clinical research, and mental health policy. CAMH’s researchers bring together their discoveries to revolutionize the understanding of the brain, use evidence to drive social change and optimize care, and inspire hope for those with mental illness in Canada and globally.

About The Krembil Centre for Neuroinformatics (KCNI:)
The Krembil Centre for Neuroinformatics (KCNI) at the Centre for Addiction and Mental Health (CAMH) is harnessing the power of high-performance computing to integrate and analyze the wealth of data generated about the brain. Our research is performed in an open science environment, with an emphasis on reproducible data-driven research and a patient-centric approach to accelerate the identification and treatment of mental illness. A focus on global collaboration is key to transforming our understanding of mental health and its treatment. The Centre operates as an incubator for medical technologies to identify, manage and treat mental illness while shaping policy at national and global levels.

CAMH is a Tobacco-Free Organization.

CAMH is fully affiliated with the University of Toronto and is a teaching hospital and research institute. As a CAMH employee, you will be expected to actively support CAMH’s teaching and research activities, in addition to supporting the clinical work of the hospital.As an employment equity employer, CAMH actively seeks Aboriginal peoples, visible minorities, women, people with disabilities, (including people who have experienced mental health and substance use challenges), and additional diverse identities for our workforce.
Research Analyst (Data Engineer)
The successful candidate will assist with ongoing national and international collaborative projects by building reproducible data extraction, transformation, loading (ETL), and machine learning/AI-based pipelines. The analytical workflows will be geared towards understanding the individualized real-world experience of mental health using multimodal data (eg - electronic medical records, sensors-based data from wearables and smartphones, etc). Specifically, the candidate will have demonstrable experience in using open-source frameworks (e.g MLFlow, Apache Airflow) to deploy cloud-based and/or on-premise ETL and analytical workflows.

The person will also have an active interest in mental health and a passion for findable, accessible, interoperable, and reusable (FAIR) data solutions in biomedical research. They will also support a workplace that embraces diversity, encourages teamwork, and complies with all applicable regulatory and legislative requirements.

The primary responsibilities of this position will involve:
- Writing computational scripts to automate data analysis, including in Python, R, and the Unix shell
- Develop end-to-end ETL and ML /AI pipelines that can run locally and/or on one or more widely used cloud platforms (AWS, Google, Azure)
- Design and implement tools and services including new APIs and libraries for serving ML/AI models to internal and external collaborators
- Maintaining high quality online documentation for computational tools and analysis workflows
- Disseminating research, either through conference presentations and/or scientific publications
- Participating in data quality control and contributing to novel data analyses using computational tools
- Communicating with and assisting team members in collaborative projects
- Assisting with administrative tasks, including meeting scheduling and preparing data use agreements
Click here to apply
ML/AI Intern - 2022 (research focused - M.Sc/Ph.D only)
The Augmented Intelligence and Digital Tech for Mental Health Group (AID4MH) (www.aid4mental.health), based at the Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health, Toronto is seeking an intern for developing and optimizing Machine Learning / Artificial Intelligence models and pipelines for enabling digital mental health research and operations.

The successful candidate will assist with ongoing national and international collaborative projects by designing and developing exploratory data analysis (EDA) pipelines on heterogeneous sensor and survey data (e.g. time series, images, text…etc.), building and testing ML feature engineering pipelines, and perfoming ML model design and optimization for specific applications, with main focus on the following:.
- Heterogeneous Data management (Time series, images, text, etc.): ingestion, preprocessing, processing, augmentation
- Manual Feature engineering: extraction, ranking and selection
- ML/AI model design (supervised, semi-supervised, unsupervised): typical feature-based approaches, and deep learning-approaches
- ML/AI model engineering: training, testing, tuning, validation, and metric visualization
The analytical workflows will be geared towards understanding the individualized real-world experience of mental health using multimodal data (e.g. electronic medical records, sensor-based data from wearables and smartphones, etc). This position is currently located at 250 College Street Site, Toronto with remote work as an option.

The primary responsibilities of this position will involve:
- Writing scripts for heterogeneous data preprocessing according to the data type and application
- Designing feature engineering pipelines for extraction, transformation, and selection
- Designing and optimizing supervised, semi-supervised, and unsupervised ML models
- Implementing state-of-the art deep learning techniques for time series classification and forecasting, and Natural Language Processing
- Implementing transfer learning to use and leverage pre-built state-of-the-art ML models
- Testing, validating, and tuning ML/AI models for optimal application-specific performance
- Communicating with and assisting team members in collaborative projects
- Communicating with team members in collaborative projects
Qualifications:
- Enrolled full time at a University/College in a Master’s/Ph.D. program (e.g. Computer Science, Software Engineering, Bioinformatics)
- Completed at least one year of CS/ML/AI-related coursework
- Demonstrable experience writing open-source computational scripts (in Python/R) for ML pipelines from data preprocessing to model tuning and validation
- Experience in using one or more of the open-source ML frameworks:
Evidence working collaboratively in a team setting is an asset. Evidence of strong written and oral communication skills and working collaboratively in a team setting are strong assets. The person will also have an active interest in mental health and a passion for findable, accessible, interoperable, and reusable (FAIR) data solutions in biomedical research. They will also support a workplace that embraces diversity, encourages teamwork, and complies with all applicable regulatory and legislative requirements.
About Krembil Centre For Neuroinformatics (KCNI):
The Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health (CAMH) is harnessing the power of high-performance computing to integrate and analyze the wealth of data generated about the brain. Our research is performed in an open science environment, with an emphasis on reproducible data-driven research and a patient-centric approach to accelerate the identification and treatment of mental illness. A focus on global collaboration is key to transforming our understanding of mental health and its treatment. The center operates as an incubator for medical technologies to identify, manage and treat mental illness while shaping policy at national and global levels.

CAMH is a Tobacco-Free Organization.

CAMH is fully affiliated with the University of Toronto and is a teaching hospital and research institute. As a CAMH employee, you will be expected to actively support CAMH’s teaching and research activities, in addition to supporting the clinical work of the hospital.As an employment equity employer, CAMH actively seeks Aboriginal peoples, visible minorities, women, people with disabilities, (including people who have experienced mental health and substance use challenges), and additional diverse identities for our workforce.

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