422 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" research jobs in Singapore
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expression systems Control of transcription, gene regulatory networks Synthetic biology, especially cell line engineering Immunotherapy, especially CAR-T/NK/M or dendritic cell therapies Diabetes, especially
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Corporate Laboratory is seeking to hire a Research Fellow. The selected candidate will innovate research in advanced materials. Key Responsibilities: Work on AI-driven techniques such as machine learning and
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). Plan and draft cross-project analyses, synthesis sections, and learning summaries to disseminate CRCD research findings through publications and events (e.g., journal sections, pre-conference sessions
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imaging, signal processing, or machine learning. Hands-on experience with ultrasound systems, particularly Verasonics platform is preferred. Familiar with programming languages and environments such as
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EEG electrodes, and administering computer-based neurobehavioral tests to research participants. Additional roles include participant recruitment and data analyses. Job Requirements Bachelor’s
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Job Description Job Alerts Link Apply now Job Title: Research Assistant (Microelectronics) Posting Start Date: 17/11/2025 Job Description: Job Description The Electrical and Computer Engineering
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based on performance and funding availability. Review of applications will begin immediately and continue until the position is filled. Qualifications • PhD Degree in Electrical and Computer Engineering
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expression systems Control of transcription, gene regulatory networks Synthetic biology, especially cell line engineering Immunotherapy, especially CAR-T/NK/M or dendritic cell therapies Diabetes, especially
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audio workflows Familiarity with VR/360 production (or strong willingness to learn) Strong organizational and communication skills Ability to work independently and collaboratively Qualifications Holds a
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) or an equivalent honours degree, or a Master’s degree in the Social Sciences. Competencies • Willingness to learn about and work with researchers using mixed methods; prior experience of working with mixed