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MOE START Scheme (Applied Research Fellowship) - Food, Chemical and Biotechnology

Singapore Institute of Technology

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About the role

Job Description MOE START Scheme (Applied Research Fellowship) - Food, Chemical and Biotechnology

Posting Start Date: 06/05/2026

Schemes of Service: Faculty

Division: Food, Chemical and Biotechnology

Employment Type: Fixed Term

At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in our education, while benefitting them with our talent supply and collaborative research achievements.

The University’s unique applied learning pedagogy integrates work and study, embedding authentic learning experiences within real-world environments. Through strategic partnerships forged by our faculty with industry, learners bridge theoretical knowledge with practical application in and out of the classroom. Such active & authentic learning opportunities ensures graduates step into their careers with applicable skills and competence.

In research, SIT faculty aims to bridge knowledge creation and utilisation. Our faculty collaborates closely with industry on translational research and innovation with focus on addressing pertinent industry challenges to impact businesses.

The Singapore Teaching and Academic Research Talent (START) Scheme is co-funded by the Ministry of Education (MOE) and SIT to encourage and support outstanding young Singaporeans interested in pursuing an academic career at SIT.

The Applied Research Fellowship aims to provide doctoral candidates who are about to complete or have recently completed their studies an opportunity to engage in advanced training and/or research at an overseas university for one year. Besides financial support, awardees will also receive academic mentorship. Upon completion of the Fellowship, awardees will be considered for Assistant Professorship. Eligibility and Selection Criteria

  • Singapore citizen
  • Doctoral candidates who have recently completed or are about to complete their studies in a discipline under the supported areas for START below
  • Excellent academic record plus a high degree of proficiency and motivation for selected research area
  • Have been accepted or have applied for a postdoctoral training at a leading overseas university in a research area that is aligned with SIT’s supported areas
  • A keen interest in an academic career

Value of Fellowship The Fellowship provides

  • Monthly stipend
  • Overseas maintenance allowance
  • Return economy airfare
  • Conference and fieldwork grants
  • Overseas medical insurance

Fellows will also each be assigned a SIT faculty mentor throughout their post-doctoral training and have opportunities to participate in faculty development programmes.

The fellowship is tenable for one year. On an exception basis, a two-year programme may be supported.

Service Commitment One year for every year of sponsorship.

Supported Areas for START - Food, Chemical and Biotechnology

  • Sustainable and Functional food: Sustainable food systems and circular food economy - alternative proteins, upcycled ingredients); AI and automation in food manufacturing - smart sensors, digital twins, and AI-driven food quality control and processing; Food safety - supply chain tracking/monitoring, blockchain
  • Biotechnology: Host strain screening and engineering for microbial bioprocess development; microbial physiology and adaptation for industrial applications; high-throughput screening and automation for strain optimization; bioprospecting for novel microbial hosts, enzymes, and metabolites to support sustainable biomanufacturing.
  • (Bio)pharmaceuticals: Processing science and technology for bio- and chemical transformations, separations, purifications and formulation applied to pharmaceuticals manufacture; modelling of processing steps and whole processes to support innovation, design, optimisation and control for manufacturing operations.
  • Process control: process modelling, control, and optimization, with applications in chemical and pharmaceutical manufacturing; data-driven modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process analytical technology (PAT); process intensification and sustainability.

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