Analyze and integrate multi-modal data (sequencing, imaging, spatial profiling, treatment response and clinical data) for translational outcomes to cancer patients

When:
15/06/2022 – 16/06/2022 all-day
2022-06-15T02:00:00+02:00
2022-06-16T02:00:00+02:00

Offre en lien avec l’Action/le Réseau : RoCED/– — –

Laboratoire/Entreprise : Bioinformatics Institute, A*STAR
Durée : 6 months
Contact : woo_xing_yi@bii.a-star.edu.sg
Date limite de publication : 2022-06-15

Contexte :
This offer is proposed by Xing Yi Woo, Head of Research Data Integration and Senior Principal Investigator at Bioinformatics Institute, A*STAR.
We work closely with clinicians to explore personalized treatment options for cancer patients using multi-omic and spatial profiling, and therapeutic screening in patient-derived models. Data of multiple modalities are generated in the process, and we are developing systematic workflows to integrate and analyze the data to enable clinical-decision-making and drive translation research. This project is looking for candidates to develop computational methods, including big-data analytics and AI/ML approaches, to analyze and integrate the multi-modal data (sequencing, imaging, spatial profiling, treatment response and clinical data) that can deliver translational outcomes to cancer patients. The candidate will have the opportunity to work in a multi-disciplinary team led by a senior Principal Investigator highly experienced in cancer computational biology and clinician-scientists specializing in oncology. Eventually, the candidate will receive training in both computational biology and translation oncology disciplines.

Sujet :
The intern is expected to work on any of these tasks, depending on field of study and interests.
1. Develop, implement and benchmark executable workflows for variant (SNP, Indels, SV, CNV) calling from WES/WGS data, transcriptome profiling from RNASeq data and image processing of histology images.
2. Write scripts to output data in a format that can be integrated with publicly available cancer datasets
3. Organize and analyze publicly available cancer datasets
4. Develop visualization tools to visualize results in a meaningful way
5. Organize all data in a structured manner using relational databases
6. Curation of cancer treatment and biomarkers, and patient clinical data.

Profil du candidat :
• The candidate should have basic programming skills (e.g. Python, R, RStudio, Jupyter Notebook, RShiny, SQL), except for curation tasks.
• Familiarity with Unix/Linux environment or cloud architecture would be an advantage
• Strong analytical and problem-solving skills.
• Excellent oral and written communication and presentation skills.
• Able to work independently, and as part of a team

Formation et compétences requises :
Computer science, any field of Science and Engineering, Pharmacy, Medicine, Public Health

Adresse d’emploi :
BII, A*STAR, Singapore