The Innovation & Enterprise Fellowship Programme (IFP) seeks to grow the pool of deep-tech talent in Singapore with the capabilities to support the commercialisation of deep-tech research and bring nascent technologies to market. Targeting researchers, scientists, and engineers (RSEs), the programme aims to develop industry relevant innovation and entrepreneurial skills through both formal and on-the-job training.
At EDDC, our goal is to discover and develop novel therapeutics by working collaboratively with the public sector and industry partners to translate innovations from bench to clinic using industry relevant and cutting-edge technology platforms. This involves addressing intricate and unexplored challenges in various disease areas, including oncology, fibrosis, infectious diseases, and autoimmune disorders. EDDC is now seeking under the IFP programme a highly motivated candidate with specialized skills in high throughput phenomics, utilizing advanced experimental and computational techniques to accelerate drug discovery and development. The position requires the implementation of methods and workflows that incorporate high-content screening, automated image analysis, and data integration from diverse phenomics datasets. The candidate will apply advanced data analysis strategies, utilizing machine learning approaches for insightful decision-making in research.
This is an eighteen-month on-the-job training programme that requires participation in and supporting cross-functional and collaborative drug discovery projects. By joining EDDC, the IFP candidate will be part of a dynamic, interdisciplinary team working to evaluate, develop and integrate high-throughput experimental data with computational methods to drive innovations in biomedical research and therapeutic development.
Responsibilities:
- Experimental Design and Execution: Develop and implement high-throughput screening protocols, particularly utilizing High-Content Screening (HCS) methodologies. This entails integrating advanced microscopy and image analysis for comprehensive cellular studies.
- Data Analysis and Interpretation: Engage in the management and interpretation of large-scale data sets derived from high-throughput experiments. Employ statistical and computational methodologies to extract significant biological insights and patterns from complex data.
- Protocol Optimization: Innovate and refine experimental procedures to enhance the efficiency and accuracy of phenomics assays. This involves systematic protocol development and validation to ensure reproducibility and reliability of results.
- Collaborative Research and Data Recording: Foster multidisciplinary collaboration in a matrix organisation. This involves working cross-functionally to evaluate, develop and integrate experimental data to drive innovations in biomedical research. Maintaining robust data record-keeping as per EDDC policy, ensuring accurate documentation, and archiving of all research data in line with SOPs.
- Continual Professional Development: Maintain an up-to-date knowledge base in the field of high throughput phenomics and related disciplines. This includes staying abreast of emerging research, technological advancements, and evolving methodologies in phenomics, thereby contributing to the ongoing development and innovation within the lab"s research endeavours.
Requirements:
- Doctorate (Ph.D.) in Cell Biology, Molecular Biology, Bioinformatics, or a closely related scientific discipline
- Extensive experience in high-throughput screening methodologies, with a particular focus on High-Content Screening (HCS).
- Proficiency in fluorescence microscopy, image-based cytometry, and the application of automated image analysis techniques.
- A strong commitment to ongoing professional growth and staying abreast of current and emerging trends in high throughput phenomics and related scientific areas.
- Exceptional ability in both written and oral communication.
- Competence in presenting complex scientific data to varied audiences, encompassing both scientific and non-scientific communities.
- Demonstrated ability in handling and interpreting large-scale biological data sets.
- Proficient in the use of statistical software and programming languages relevant to bioinformatics, such as R and Python.
- A proven track record in designing and executing biological experiments.
- Evidence of scholarly contribution through peer-reviewed publications in relevant scientific fields.
- Experience in working within multidisciplinary research teams.
- Demonstrated skill in effective collaboration with both internal team members and external research partners.
- Ability to innovate and develop novel methodologies and technologies to advance phenomics research.
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.
