Research Officer, Laboratory of Regulatory Genomics (GIS)
Salary undisclosed
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The successful candidate will be responsible for processing and analyzing large-scale single-cell and spatial transcriptomics datasets, developing computational pipelines, and collaborating closely with researchers across different disciplines. Strong communication and analytical skills are essential, as the role involves working with experimentalists, clinicians, and data scientists to interpret and visualize complex omics data.
Key Responsibilities
? Process, analyze, and interpret single-cell RNA-seq and spatial transcriptomics data from skin samples.
? Develop and implement computational pipelines using R and/or Python for large-scale omics data analysis.
? Perform statistical modeling and machine learning approaches to identify patterns and functional insights.
? Work closely with experimentalists, dermatologists, and computational scientists to integrate findings and generate biologically meaningful insights.
? Manage, curate, and visualize complex datasets for effective communication of results.
? Contribute to manuscript preparation, grant writing, and presentations.
? Keep up to date with the latest computational methodologies and tools in single-cell and spatial omics research.
Qualifications & Skills
Essential:
? MSc or BSc (with equivalent experience) in Bioinformatics, Computational Biology, Data Science, Genomics, or a related field.
? Strong proficiency in R and/or Python for bioinformatics data analysis.
? Good understanding of statistics, machine learning, and high-dimensional data analysis.
? Experience working with large omics datasets, including single-cell RNA-seq and/or spatial transcriptomics.
? Strong analytical and problem-solving skills.
? Excellent written and verbal communication skills, with the ability to work collaboratively in a multidisciplinary team.
Desirable:
? Experience in spatial transcriptomics and imaging-based omics analysis.
? Familiarity with cloud computing and high-performance computing environments.
? Knowledge of biological pathways and skin biology.
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.
Type of Employment : Full-Time
Work Location : Biopolis
Key Responsibilities
? Process, analyze, and interpret single-cell RNA-seq and spatial transcriptomics data from skin samples.
? Develop and implement computational pipelines using R and/or Python for large-scale omics data analysis.
? Perform statistical modeling and machine learning approaches to identify patterns and functional insights.
? Work closely with experimentalists, dermatologists, and computational scientists to integrate findings and generate biologically meaningful insights.
? Manage, curate, and visualize complex datasets for effective communication of results.
? Contribute to manuscript preparation, grant writing, and presentations.
? Keep up to date with the latest computational methodologies and tools in single-cell and spatial omics research.
Qualifications & Skills
Essential:
? MSc or BSc (with equivalent experience) in Bioinformatics, Computational Biology, Data Science, Genomics, or a related field.
? Strong proficiency in R and/or Python for bioinformatics data analysis.
? Good understanding of statistics, machine learning, and high-dimensional data analysis.
? Experience working with large omics datasets, including single-cell RNA-seq and/or spatial transcriptomics.
? Strong analytical and problem-solving skills.
? Excellent written and verbal communication skills, with the ability to work collaboratively in a multidisciplinary team.
Desirable:
? Experience in spatial transcriptomics and imaging-based omics analysis.
? Familiarity with cloud computing and high-performance computing environments.
? Knowledge of biological pathways and skin biology.
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.
Type of Employment : Full-Time
Work Location : Biopolis