Senior Computational Biologist (Genomics Focus)

Placements24; Willows (CA); Hybride; USD 55 000 - 91 000; Plein temps

Avantages offerts par ce poste

Medical, dental, and vision

Retirement plan

Advanced computational resources

Professional development

Hybrid work model

Résumé du poste

Placements24 is seeking a Senior Computational Biologist with a genomics focus to join a biotech team in Welkom, Free State. The role centers on building pipelines, analyzing large genomic datasets, and collaborating with clinicians to translate findings into disease insights.

The candidate will mentor junior team members, develop predictive models for disease risk and drug response, and stay at the forefront of computational biology and bioinformatics technologies.

Qualifications

• PhD in Computational Biology, Bioinformatics, Genomics, CS, or related field.
• 6+ years post-PhD experience in computational biology focusing on genomics.
• Proficiency in Python, R, or Perl and NGS data analysis tools (GATK, STAR, DESeq2).

Responsabilités

• Develop and implement bioinformatics pipelines for NGS data (WGS, WES, RNA-seq).
• Analyze genomic and transcriptomic data to identify variations and expression patterns.
• Collaborate with biologists and clinicians to design studies and interpret results.
• Develop statistical models to analyze complex biological data.
• Mentor junior computational biologists and provide guidance.
• Maintain and optimize bioinformatics tools and databases.

Connaissances

Genomics

Post-doc/Industry experience

Python

R

Perl

Statistical modeling

Machine learning

Team collaboration

Communication

Formation

PhD in Computational Biology or related field

Outils

GATK

STAR

DESeq2

Description du poste

About the Role

Our client, a leading biotechnology firm at the forefront of genetic research, is seeking a highly skilled Senior Computational Biologist with a strong focus on genomics to join their innovative team in Welkom, Free State . This role is essential for driving forward our understanding of complex biological systems through the analysis of large-scale genomic datasets. The successful candidate will leverage advanced computational tools and statistical methods to uncover insights into disease mechanisms, drug discovery, and personalized medicine. This is a fantastic opportunity to contribute to significant advancements in life sciences within a collaborative and research-intensive environment.

Key Responsibilities

• Develop and implement bioinformatics pipelines for the analysis of next-generation sequencing (NGS) data, including WGS, WES, and RNA-seq.
• Perform in-depth analysis of genomic and transcriptomic data to identify genetic variations, gene expression patterns, and regulatory networks.
• Collaborate with experimental biologists and clinicians to design studies, interpret results, and address biological questions.
• Develop and apply statistical models to analyze complex biological data and draw meaningful conclusions.
• Contribute to the development of predictive models for disease risk, drug response, and patient stratification.
• Visualize complex biological data to effectively communicate findings to both technical and non-technical audiences.
• Maintain and optimize existing bioinformatics tools and databases.
• Stay current with the latest advancements in computational biology, genomics, and bioinformatics.
• Mentor junior computational biologists and provide technical guidance.
• Document methodologies, analyses, and results thoroughly for reproducibility and publication.

Requirements

• Ph.D. in Computational Biology, Bioinformatics, Genomics, Computer Science, Statistics, or a related quantitative field.
• A minimum of 6 years of relevant post-doctoral or industry experience in computational biology, with a strong emphasis on genomics.
• Proficiency in programming languages commonly used in bioinformatics, such as Python, R, or Perl.
• Hands-on experience with NGS data analysis tools and software (e.g., GATK, STAR, DESeq2, etc.).
• Strong understanding of statistical methods and machine learning techniques applicable to biological data.
• Experience with large-scale data management and high-performance computing environments.
• Familiarity with various biological databases (e.g., NCBI, Ensembl, UCSC Genome Browser).
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication and collaboration skills, with a proven ability to present complex data effectively.
• Knowledge of biological pathways and disease mechanisms is a significant advantage.

Benefits

• Competitive salary, commensurate with experience, along with performance incentives.
• Medical, dental, and vision coverage.
• Retirement savings plan.
• Employees have access to advanced computational resources and state-of-the-art laboratory facilities in Welkom, Free State.
• Opportunities for professional development, including attending conferences and workshops, are readily available.
• This hybrid role provides a flexible work arrangement, balancing on-site collaboration with remote work.
• Join a team that is making significant strides in understanding human health and disease through cutting-edge genomic research.