Research Scientist - Genomics and Computational Biology

Placements24; South Africa; Remote; ZAR 1,488,000 - 2,479,000; Full time

Benefits offered by this job

Competitive salary

Full remote work

Professional development

Job summary

Placements24 is seeking a Research Scientist to join a fully remote team focused on Genomics and Computational Biology. You will advance understanding of complex biological systems by analyzing large-scale genomic data and applying innovative computational methods.

Collaborating with scientists globally, you will design pipelines for WGS/WES/RNA-Seq, apply ML and statistical techniques, and contribute to publications and discoveries from a remote setting.

Qualifications

• Ph.D. or Master’s in Genomics, Bioinformatics, Computational Biology, Statistics, or a related quantitative field.
• 3+ years of experience analyzing large-scale genomic data.
• Proficiency in Python or R and relevant bioinformatics libraries.

Responsibilities

• Design and implement bioinformatics pipelines for WGS, WES, and RNA-Seq.
• Apply statistics and machine learning to identify variants and expression patterns.
• Collaborate with clinicians to integrate computational findings with experimental data.
• Develop predictive models and algorithms to uncover mechanisms and targets.
• Prepare findings for publication and presentation.
• Maintain and optimize computational workflows and explore new analyses.

Skills

Communication

Collaboration

Education

Ph.D. in Genomics or related field

Master's in Genomics or related field

Tools

Python

R

Job description

About the Role

Our client is looking for a dedicated Research Scientist to join their fully remote team, focusing on the synergistic fields of Genomics and Computational Biology . This position is crucial for advancing our understanding of complex biological systems through the analysis of large-scale genomic data. You will play a key role in developing and applying innovative computational methods to drive scientific discovery and accelerate research programs. This is an exceptional opportunity to contribute to impactful research from a remote setting, collaborating with a talented and diverse team of scientists who are passionate about pushing the boundaries of biological science and improving health outcomes.

Key Responsibilities

• Design and implement bioinformatics pipelines for the analysis of diverse genomic datasets, including whole-genome sequencing (WGS), exome sequencing (WES), and RNA-Seq.
• Apply statistical and machine learning techniques to identify genetic variations, gene expression patterns, and functional genomics insights.
• Collaborate with experimental biologists and clinicians to integrate computational findings with biological context and experimental data.
• Develop predictive models and algorithms to uncover novel biological mechanisms and potential therapeutic targets.
• Contribute to the interpretation of results and the preparation of findings for publication and presentation.
• Maintain and optimize existing computational workflows and explore new analytical approaches.

Requirements

• Ph.D. or Master's degree in Genomics , Bioinformatics, Computational Biology, Statistics, or a related quantitative field.
• Proven experience (3+ years) in analyzing large-scale genomic data using computational and statistical methods.
• Proficiency in programming languages such as Python or R, and experience with relevant bioinformatics libraries and databases.
• Strong understanding of molecular biology, genetics, and common genomics technologies.
• Experience with Linux/Unix environments and cloud computing platforms is highly preferred.
• Excellent communication and collaboration skills for effective teamwork in a remote environment.

Benefits

• Competitive salary and a comprehensive benefits package.
• Full remote work flexibility with dedicated support.
• Opportunities for professional growth and continuous learning.
• Contribution to significant research in genomics and computational biology.
• A collaborative and innovative virtual research environment.
• Access to cutting-edge computational tools and resources.