Job Description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com

Job Function:

Career Programs

Job Sub Function:

Post Doc - Data Analytics & Computational Sciences

Job Category:

Career Program

All Job Posting Locations:

Toronto, Ontario, Canada

:

Description:

The Data Science Analytics & Insights team is actively searching for a highly motivated


and visionary postdoctoral researcher, with a primary research focus on innovative


Artificial Intelligence/Machine Learning (AI/ML) algorithms to extract valuable insights


from structured and unstructured multimodal data sources. We are particularly


interested in candidates with expertise in speech analysis and/or natural language processing (NLP) and a deep passion for making a meaningful impact through their work. Your contributions will involve developing and validating AI/ML solutions to solve complex problems across various therapeutic areas within the organization.

Key responsibilities:

Conceive, develop, and validate AI/ML solutions for high-priority scientific

research projects.
Extract, analyse and interpret multimodal data (including speech and/or text) from various sources. Participate in cross-functional collaborations with internal stakeholders and

external partners.
Clearly communicate the state-of-the-art methods and results to diverse audiences

and partners to support decision-making.
Publish findings in top-tier journals and conferences.

Required qualifications:

A Ph.D. degree in AI/ML or a related field (e.g., computational linguistics,

computational biology, computational neuroscience, computer science, data


science, applied mathematics, statistics, electrical engineering, signal


processing) obtained within the last 2 years or to be completed within the next 3


months.
Proven track record of applying advanced AI/ML techniques, supported by

publications in peer-reviewed journals and conferences.
Experience with standard analytical techniques (e.g., logistic regression, support

vector machines, random forest, boosting, ensemble methods) and advanced AI


methodologies (e.g., convolutional neural networks, recurrent neural networks,


attention models, transformers).
Experience with acoustic speech analysis techniques and models (e.g., openSMILE, librosa, Whisper, HuBERT, WavLM, wav2vec). Experience with basic and advanced NLP techniques (e.g., word2vec, wav2vec,

Whisper, BERT, GPT) and its applications in linguistic analysis.
A good understanding of various speech features (acoustic and linguistic) and their corresponding constructs that they capture (e.g., speech timing). Experience with applications of LLMs to acoustic and linguistic analysis would be a plus. Knowledge of statistical methods. Proficiency in one or more programming languages (e.g., Python). Experience with software development tools (e.g., Git). Analytical mindset and critical thinking. Ability to continuously learn and acquire new knowledge and skills. Ability to optimally communicate technical work to a wide and diverse audience,

both in oral and written forms.
Ability to work both independently and in a diverse, multidisciplinary team. Passionate about leveraging data to drive scientific innovation.

Preferred ("nice-to-have") qualifications:

Experience in analysing speech and actigraphy data. Experience in analysing biomedical data. Background in biology or a related field (e.g., neuroscience). Expertise in one or more disease areas (e.g., mental health). Familiarity with the processes of drug discovery, safety and development. * Experience in analysing speech recorded during conversations (e.g., recorded during interview).