Job description
We are looking for highly-motivated and enthusiastic individuals with good AI/machine learning/deep learning skills to work on a new initiative on developing an AI approach for scoring of tumor epitope immunogenicity, aiming to better inform the cancer vaccine formulation and predict treatment response.
Successful candidate will work with a multidisciplinary team of bioinformaticians, immunologists, technical scientists, and oncologists to adopt, benchmark, and/or develop novel AI approaches which enable effective integration of multi-omics data (including whole-exome sequencing, RNA sequencing, proteomics, spatial-omics, immuno-peptidomic, and histological image data) for the prediction/ranking of tumor epitope immunogenicity. Successful candidate will have the opportunity to tap into a large pool of biomedical data of various forms and to establish a niche research area in AI-enabled (spatial) multi-omics cancer study.
Job requirements:
- Bachelor degree in the field of bioinformatics, computer science, computer engineering, or other data science intensive program. With expertise in at least one of the following areas: bioinformatics, data mining, machine and statistical learning, deep learning
- Possess minimum 5 years of relevant work experience
- Ability to work independently to translate research ideas into programs with efficient coding
- Basic knowledge on biology, data analytics, machine learning, deep learning
- Proficient in Python or R
- Deep learning programming skill is a plus
- Able to deliver under tight schedule
- Good team player with both research and data analytics ethics
- Good interpersonal and communication skills
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.
