Confident self-starter with initiative and capable of working successfully within a team and with key stakeholders in the ecosystem
Excellent interpersonal communication, organisational and administrative skills
SingHealth's expanding portfolio in research partnerships, innovation development and commercial collaborations has driven the need for robust governance in managing complex conflict of interest matters. This exciting opportunity calls for an experienced professional to establish and lead a dedicated Conflict of Interest Unit within our Technology Development & Commercialisation (TD&C) team. The role offers the chance to shape institutional policy and practice while supporting our healthcare professionals in their research, innovation and industry partnerships.
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Liaise with faculty, research staff, internal University offices and grant team members to obtain required information and follow up on pending items.
Degree in any discipline, preferably in business, administration, science or a related field.
Preferably 1 to 3 years of relevant administrative, research, finance, grant support or coordination experience; candidates with strong administrative experience and willingness to learn may be considered.
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Accountable for timely start-up activities from country allocation until site greenlight at assigned Sites. Conducts site selection visits, verifies site eligibility for a specific study
Main contact for trial sites during site selection, study start-up and IRB/IEC and HA submission. Preparation. Ensures that milestones (KPIs) and time schedule for study start-up are met as planned
Supports SSU Manager in preparation of country-specific documents, e.g., ICF, patient facing materials, etc. Supports SSO Study Start-Up Manager and assigned sites in vendor set-up activities
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Provide technical and product leadership across the end-to-end AI lifecycle, from research, experimentation and prototyping through production deployment, monitoring and continuous improvement.
Ensure AI solutions are scalable, secure, reliable and fit for purpose, balancing technological innovation with user needs, operational requirements, governance standards and organisational roadmaps.
Establish best practices in AI engineering, model evaluation, Responsible AI, MLOps and AI product delivery to ensure high-quality, trusted and sustainable AI systems.
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