Senior Research Engineer - Data Scientist

Project Overview

This role centers on advancing a cutting-edge real-time blood diagnostic platform utilizing an integrated microfluidic medical device. The technology profiles white blood cell activity linked to inflammatory diseases including diabetes, sepsis, and leukemia.

Role Summary

The Senior Research Engineer / Data Scientist will spearhead the acquisition, processing, analysis, and modeling of data generated by the medical device. Collaboration with clinicians, scientists, and engineers is essential to turn AI and machine learning research into deployable clinical software.

Key Responsibilities

• Collaborate with a multidisciplinary team to define clinical requirements, data inputs, and outputs relevant to device deployment.
• Create robust data acquisition systems for hardware and sensor outputs, including imaging and signal data alongside associated metadata.
• Build preprocessing pipelines with quality controls and feature engineering designed for complex, multimodal biomedical datasets.
• Conduct comprehensive data analyses to validate device and biological signals, detect artifacts, and benchmark performance for translational studies.
• Develop and optimize statistical, machine learning, and hybrid models, ensuring cross-validation, uncertainty estimation, and robust evaluation metrics.
• Convert research models into reproducible software components such as inference pipelines, APIs, dashboards, and user interfaces tailored for clinical usage.
• Support integration of software and hardware components, refining user experience based on clinician feedback for prototype deployment.
• Maintain complete documentation including codebases, data dictionaries, experimental protocols, validation results, and technical reports.
• Author scientific manuscripts, presentations, and grant materials; assist in patent searches and responsible dissemination of research findings.
• Coordinate clinical study data workflows, ensuring adherence to data governance and privacy standards.

Candidate Requirements

• Possess over three years educational background in fields like Data Science, AI/ML, Biomedical Engineering, Bioinformatics, Statistics, or related disciplines; candidates nearing degree completion considered.
• Proven research experience in biomedical data science, machine learning, signal/image processing, clinical AI, or related computational roles.
• Advanced proficiency with Python programming and scientific computing libraries (NumPy, pandas, scikit-learn) and machine learning frameworks (PyTorch, TensorFlow).
• Experience handling data pipelines encompassing acquisition, cleaning, feature extraction, modeling, and software reproducibility.
• Knowledge of clinical or biomedical datasets, medical device data, biosensors, and multimodal signal processing highly regarded.
• Ability to translate ML models into practical software deliverables such as RESTful APIs and interactive dashboards.
• Familiarity with hardware interfacing, embedded systems, communication protocols (USB, Bluetooth), and edge AI deployments is a plus.
• Excellent communication abilities for documenting technical content and presenting to cross-functional teams.
• Demonstrated commitment to ethical AI practices including privacy, bias mitigation, interpretability, and clinical safety.
• Willingness to be based in Singapore and engage regularly with collaborators at academic and clinical institutions.

Relevant Expertise

Skills encompassing Python, data acquisition techniques, biomedical signal and time-series analysis, machine learning frameworks, data preprocessing, explainable AI, software-hardware integration, and clinical data governance are pertinent.