Senior Computational Biologist - Remote & Flexible Hours

Placements24; United States; Hybrid; USD 73,000 - 110,000; Full time

Benefits offered by this job

Flexible working hours

Remote work options

Medical aid and retirement fund

Professional development support

Access to HPC resources

Job summary

Placements24 is seeking a Senior Computational Biologist to lead analysis of genomics, transcriptomics, and proteomics datasets. You will build and apply advanced computational methods and ML to uncover insights and guide research directions.

The role involves close collaboration with experimental teams to translate computational findings into testable hypotheses and experimental designs, with flexible hours and remote work options available.

Qualifications

• PhD in Computational Biology, Bioinformatics, CS, Statistics or related quantitative field.
• Minimum of 5 years of experience in computational biology research with large-scale datasets.
• Proficiency in Python or R and experience with bioinformatics tools/databases.
• Strong statistical modeling, ML techniques, and data visualization skills.
• Excellent problem-solving and collaboration in a research environment located in Rustenburg.

Responsibilities

• Design and implement computational pipelines for high-throughput omics data.
• Develop and apply statistical and ML models to identify patterns and targets.
• Collaborate with experimental scientists to translate findings to hypotheses and validation strategies.
• Visualize and communicate complex data to technical and non-technical audiences.
• Stay updated with advances in computational biology and bioinformatics.

Skills

Python

R

Statistical modeling

Machine learning

Data visualization

Problem solving

Education

PhD in Computational Biology

Tools

Bioinformatics tools

Biology databases

Job description

Placements24 is seeking a Senior Computational Biologist to lead analysis of genomics, transcriptomics, and proteomics datasets. You will build and apply advanced computational methods and ML to uncover insights and guide research directions.

The role involves close collaboration with experimental teams to translate computational findings into testable hypotheses and experimental designs, with flexible hours and remote work options available.