Auristone is an Asian-based epigenomic profiling company with data analytics capabilities that spun out from Genome Institute of Singapore (GIS) in 2021 with the vision to be the largest curator of Asian Epigenomic database to drive epigenomic discoveries. We are currently seeking a Data Scientist/Bioinformatician to join this new effort in building the epigenomics database engine to drive novel therapies and diagnostics. The company flagship product EPI-Call is a chemo-sparing predictive test for responders to immunotherapy. It integrates our proprietary Alternate Promoter Burden (APB) platform and proprietary algorithm, which is developed in-house and validated using over five hundred (500) patient samples.
The candidate will support the development of clinical grade predictive models based on both new and existing epigenetic data for predicting patient response to immunotherapy (IO) in gastric cancer patients. The candidate will work with genomics data generated from cutting-edge technologies (eg: FFPE RNA-Seq, ChIP-Seq etc), and will be involved in product development strategy, innovation activities, and commercialization efforts towards building this database engine. This role will provide a unique opportunity to apply machine learning and computational biology expertise towards developing clinical grade cancer diagnostic tests to improve outcomes for cancer patients.
Job responsibilities:
1. Analysing sequencing data for the development of cancer diagnostic tests (eg. RNA-Seq, ChIP-Seq).
2. Assembling and analysing (epi)genomics data to obtain insights on 1) predict risk of cancer development and cancer progression and 2) provide personalized, molecularly driven therapeutic recommendations.
3. Collaborating with clinicians and scientists from local and international research institutions.
4. Contribute to the building, enhancing, and curating in-house databases of sequencing data drawing from both internal and external data sets (e.g. exome/genome/transcriptome sequencing etc).Perform basic data management and cataloguing of all sequencing data.
Skills/Background
1. An advanced degree in a Computer Science/Biology related field (e.g. Bioinformatics, computer science, statistics, computational biology, genetics, etc.). Working experience in these fields may also be considered.
2. Candidates with and without postdoctoral experience will be considered.
3. Strong programming skills (Python and/or R preferred). Experience with tools such as Jupyter and RStudio will be valuable.
4. Experience working within a UNIX/Linux environment.
5. Skills related to machine learning and statistical modelling.
6. Knowledge in data engineering will be advantageous.
7. Knowledge in model productionisation with skillsets in ML Ops, DevOps or software engineering will be advantageous.
8. Experience with next generation sequencing data analysis (e.g. whole exome/whole-genome sequencing, RNA-seq, scRNA-seq, MethylSeq etc.), especially for human cancers, will be advantageous.
9. Good interpersonal skills and a team player.
#J-18808-Ljbffr