Research Fellow (Health Data Analytics)

Responsibilities

• Support the DMAC lead and Manager in the day to day administrative functions
• Provide technical contributions in a fast paced team environment to accelerate our efforts on building an analytics driven product pipeline
• Perform independent statistical analysis, computer programming, predictive modelling, and contribute to new studies
• Build cross-functional relationships to collaboratively partner with the other collaborators and effectively network within the Data Science community
• Use advanced mathematical models and machine learning to deliver insight, recommendations and solutions to different projects within UZIMA-DS project
• Contribute to the development of code, computational tools and databases for mining and visualizing large data sets resulting from maternal newborn and child health as well as mental health studies
• Develop sustainable, consumable, accurate and impactful reporting on model inputs and outputs
• Use the project data and resources to develop a PhD thesis and scientific papers leading to the award of the doctoral degree

Requirements

• Holder of Master’s Degree and currently pursuing a PhD in Computer Science, Statistics/Biostatistics, Mathematics or equivalent in a recognized university
• Proficiency using one or more programming or scripting languages such as Python, R, MATLAB, Perl, SAS or C#
• Skills in Artificial Intelligence/Machine Learning methods, data integration and mathematical modeling as well as proficiency in ETL tools
• Experience in data management in relational databases such as MySQL
• Experience in data analysis using STATA, R, or other statistical software
• Experience working with longitudinal studies, handling large data sets and cloud computing: GCP, MS Azure is desirable
• Experience in visualizing/presenting data for stakeholders and the use of relevant data visualization tools
• Experience with relevant technologies e.g. Tensor Flow, Apache Flume, machine learning libraries
• Relevant professional experience with applied data analytics and predictive modeling

Method of Application

Application letter together with detailed Curriculum Vitae, names of three referees, should be sent to the Manager, Talent Acquisition, Aga Khan University, via the email: [email protected] by 30th November 2022.

Please quote the position title on the email subject. Only short-listed candidates will be contacted.