Senior Data Scientist

Full time fixed term contract for 12 months in the first instance, with possibility of extension An exciting opportunity in a newly created role within the team focused on wearables and health within the Charles Perkins Centre and the Faculty of Medicine and Health Base Salary ranging from $104, 633 to $113,992 + 17% superannuation About the opportunity The University of Sydney, Charles Perkins Centre - Since our inception 160 years ago, the University of Sydney has led to improve the world around us. We believe in education for all, and that effective leadership makes lives better. These same values are reflected in our approach to diversity and inclusion and underpin our long-term strategy for growth. We are Australia's first university and have an outstanding global reputation for academic and research excellence. Across our campuses, we employ over 8,100 academic and non-academic staff who support over 73,000 students.
Charles Perkins Centre is at the forefront of multidisciplinary research and education and undertakes high-impact research that anticipates the cardiometabolic health issues of tomorrow while overcoming the challenges of today.
We are seeking to employ an enthusiastic, talented, and passionate Data Scientist (HEO 7) to provide technical support and leadership to the research team of Professor Emmanuel Stamatakis. This is an excellent opportunity for an outstanding Senior Data Scientist to develop a strong career in health-related research and gain substantial experience and receive training on wearables-based measurement of physical activity and sleep. The position is located at Charles Perkins Centre, a leading multidisciplinary research institute of the University of Sydney, the incumbent will support the activities within the newly founded Mackenzie Research Wearables Hub at Charles Perkins Centre.
Your key responsibilities will be: Analyse and process multimodal sensor data collected from wearables such as ECG, altimeter, accelerometer, gyroscope, polysomnography (PSG), and EMG. Work with data from wearables worn on various body locations (wrist, thigh, chest, head), including nanopolymer technology. Apply machine learning techniques such as supervised, semi-supervised, deep learning, reinforcement learning, transfer learning etc. to enhance activity recognition. Collaborate with research teams across multiple studies to ensure accurate data collection, labelling, and quality control. Manage large datasets and conduct data preprocessing, feature extraction, and model validation using appropriate statistical and computational methods. Develop and refine signal processing algorithms to handle data from complex wearables, including ECG, EEG, and EMG signals. Implement and optimize activity classification algorithms for highly variable activities, including sleep stages, daily activities, and specialized movements (e.g., stair climbing, gym workouts). Perform cross-validation, error analysis, and model tuning to ensure high accuracy in real-world applications. Stay updated on the latest developments in wearable technology and machine learning to improve current methodologies and propose innovative solutions. About you To be successful in this role, you will have: Honors or master's degree in data science, with relevant experience in a related field, or degree in a related area and substantial experience as research assistant/research officer. Experience working in a research-intensive environment. Strong background in machine learning (e.g., classification, supervised and semi-supervised learning, transfer learning) and signal processing. Expertise in working with wearable sensor data such as ECG, accelerometers, gyroscopes, PSG, EMG. Proficiency in Python, R, or other relevant programming languages. Experience with tools for time-series analysis and signal processing (e.g., scikit-learn, TensorFlow). Experience developing models using multimodal sensor data from wearables placed on different body locations. Strong understanding of biomedical signal processing and familiarity with bioinformatics tools. Knowledge of handling and analysing large datasets, with experience in data wrangling, data visualization, and feature engineering. Good inter-personal skills and capacity to resolve challenging situations in the most professional manner. Familiarity with nanopolymer technology in wearables would be desirable. Possess a capacity to work against deadlines in a fast-paced and vibrant research environment. Willingness and capacity to occasionally (e.g. 1-2 times per month on average) work out of regular office hours to accommodate the multiple time zones of the Team's international collaborators. To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus. Sponsorship / work rights for Australia Please note: Visa sponsorship is not available for this position. For a continuing position, you must be an Australian or New Zealand citizen or an Australian Permanent Resident.
Australian Temporary Residents currently employed at the University of Sydney may be considered for a fixed term contract for the length of their visa, depending on the requirements of the hiring area and the reasons for the position.
Pre-employment checks Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.
EEO statement At the University of Sydney, our shared values include diversity and inclusion and we strive to be a place where everyone can thrive. We are committed to creating a University community that reflects the wider community that we serve. We deliver on this commitment through our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ. We welcome applications from candidates from all backgrounds.
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The University of Sydney is committed to diversity and social inclusion. Applications from people of culturally and linguistically diverse backgrounds; equity target groups including women, people with disabilities, people who identify as LGBTIQ; and people of Aboriginal and Torres Strait Islander descent, are encouraged.
The University reserves the right not to proceed with any appointment.
The University of Sydney may conduct routine pre-employment checks before an appointment is made.
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