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:
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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
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Possess minimum 1 year of relevant work experience
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Ability to work independently to translate research ideas into programs with efficient coding
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Basic knowledge on biology, data analytics, machine learning, deep learning
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Proficient in Python or R
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Deep learning programming skill is a plus
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Able to deliver under tight schedule
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Good team player with both research and data analytics ethics
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Good interpersonal and communication skills
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