Senior Research Engineer, Healthcare And Medtech Division, I2R
A research engineer position is available immediately at the Institute for Infocomm Research (I2R), A*STAR, Singapore. The position will focus on developing data engineering, data mining and machine learning pipelines for applications in digital health and precision medicine.
Candidates should have strong expertise in two or more of the following areas:
- Data engineering, data analytics and data visualization
- Health informatics
- Statistics, probability or related areas in applied mathematics
- Artificial intelligence (AI) or machine learning (ML) approaches, as applied to large healthcare datasets
Ideal candidates should also have demonstrated interests or experience in one or more of the following areas:
- Analysis of large-scale real-world healthcare datasets (spanning electronic health records, lifestyle, and -omics data)
- Extract Transform Load (ETL) processes, workflows and pipelines, as applied to large or multimodal health datasets
- Application of the above processes to advanced AI/ML systems
Core responsibilities include (a) exploration, sensemaking and preprocessing of raw disparate healthcare datasets, (b) design and development of data preparation and ETL workflows and pipelines to leverage large multimodal healthcare datasets for AI/ML solutions, (c) development of automated knowledge extraction and feature engineering pipelines, and (d) translation to various downstream AI model development, inference and evaluation tasks. The position entails working in a highly inter-disciplinary R&D team in close collaboration with experts in machine learning, public health, precision medicine as well as with clinicians, health ecosystem stakeholders, and government entities on ambitious projects that have the potential to transform patient care and deliver improved health outcomes.
Job requirements include:
- Bachelors/Masters degrees in Computer Science, Statistics, Biomedical Engineering, Biomedical/Health Informatics, Computational/Systems Biology or other Data Science intensive fields.
- Strong data science, data engineering, and programming abilities, and working experience in two or more of the following areas:
- Large-scale data exploration, data engineering, data warehousing, and/or databases
- Biomedical/healthcare/clinical data preprocessing and analysis
- Knowledge extraction and feature engineering
- Machine learning methods (including application of state-of-the-art techniques)
- Deep interest in biomedical informatics, algorithm development, and experience with relevant healthcare applications highly encouraged.
- Ideally 2 years post degree completion.
- Experience in healthcare, corporate or application oriented research environments is a plus.
Additionally, candidates should:
- Be able to work independently and as part of highly interdisciplinary teams
- Be a quick and independent learner; able to acquire the necessary domain knowledge
- Have good communication skills (e.g., for presentations and reports)
- Have strong communication and excellent writing skills
- Demonstrate rigorous analytical thinking, knowledge of research methods
- Be agile in dynamic project environments with an impact-oriented mindset
- Have strong programming abilities (e.g. Python, Bash, PySpark, R, C/C++, Java, Perl)
- Have experience with data preprocessing, data science, and data visualization tools (e.g., SAS, Tableau, PowerBI, Knime, WEKA, Jupyter notebooks etc)
- Be comfortable within cloud-based data engineering and ML environments
- Have experience with biomedical informatics/healthcare data analytics, knowledge representation and model development frameworks
- Be familiar with ML/DL frameworks (e.g., PyTorch or TensorFlow)
- Have exposure to text analytics, natural language processing, text mining desirable
- Have interest in MLOps/DevOps infrastructure and pipelines for deploying AI/ML solutions for healthcare applications encouraged
- Have cross-disciplinary research experience would be advantageous
- Be motivated applicants with significant domain expertise and strong programming skills who are looking to switch into AI-related fields and committed to building robust and scalable approaches for population-scale healthcare impact
The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.