Associate Director, Oncology Genomics

TN Germany; Heidelberg; Vor Ort; EUR 80.000 - 120.000; Vollzeit

Zusammenfassung

An established industry player is seeking an Associate Director of Oncology Genomics to join their innovative team in Heidelberg. This pivotal role involves analyzing large-scale somatic genomic data and developing automated methods for bioinformatics analysis. The ideal candidate will possess a PhD and extensive experience in cancer research and data integration, showcasing strong leadership and communication skills. Join a forward-thinking organization committed to advancing oncology genomics and making a significant impact on patient health. Embrace the opportunity to lead multidisciplinary teams and contribute to groundbreaking research in a collaborative environment.

Qualifikationen

• PhD in a quantitative subject with 8+ years of experience required.
• 3+ years of programming experience in Bash, R, Python, and bioinformatics tools.

Aufgaben

• Analyze large-scale genomic datasets and derive biological insights.
• Lead multidisciplinary teams and communicate complex ideas effectively.

Kenntnisse

Bioinformatics

Programming (Bash, R, Python)

Data Analysis

Cancer Research

Communication Skills

Problem-Solving

Project Management

Ausbildung

PhD in Bioinformatics or related field

Tools

bcftools

Nextflow

Jobbeschreibung

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Associate Director, Oncology Genomics, Heidelberg

Client:

1925 GlaxoSmithKline LLC

Location:

Job Category:

Other

EU work permit required:

Yes

Job Reference:

e2f34cab47b0

Job Views:

1

Posted:

25.04.2025

Expiry Date:

09.06.2025

Job Description:

We are seeking a highly skilled and experienced individual to join our team as an Associate Director of Oncology Genomics. The successful candidate will have a key role in the analysis of large-scale somatic genomic and clinical data, applying cutting edge algorithms and developing automated methods to support large-scale bioinformatics analysis. They will be involved in the processing and analysis of NGS data (with a focus on WES/WGS, SNVs/CNVs, ctDNA) and will need a solid understanding of computational approaches for cancer genome analysis and cancer biology to derive meaningful and reproducible biological insights. Experience in complex molecular data integration, such as transcriptomics, proteomics, and metabolomics, and in deriving insights from such analyses will be advantageous. The successful candidate will be leading multidisciplinary teams to answer complex scientific questions and will have strong communication skills and the ability to convey complex ideas and concepts to a range of stakeholders, including peers and leaders.

Key Responsibilities:

1. Process and analyse large scale somatic genetic datasets (WES/WGS, SNVs, CNVs) and integrate with clinical/phenotypic datasets to derive biological insights.
2. Develop automated methods to support large scale somatic genetic, bioinformatic analyses and collaborate closely with other teams (statistical genetics/AIML) to develop advanced algorithms and models.
3. Integrate complex molecular data (e.g. transcriptomics, proteomics, metabolomics) to derive insights and understand the underlying biology.
4. Lead multidisciplinary teams effectively to answer complex scientific questions.
5. Communicate complex ideas and concepts to a range of stakeholders, including peers and leaders.
6. Collaborate with cross-functional teams to support the development and implementation of oncology genomics strategies.
7. Stay up-to-date with the latest advancements and trends in oncology genomics and molecular data integration.
8. Evaluate and implement new methodologies and technologies to improve the efficiency and effectiveness of data analyses.
9. Foster a culture of collaboration, innovation, and continuous learning within the team.
10. Ensure compliance with relevant regulations and guidelines in the field of oncology genomics.

Why you?

Basic Qualifications:

1. PhD in a quantitative subject e.g. Bioinformatics, Biostatistics, Computational Biology, Epidemiology with combined academic and or industry experience of 8+ years.
2. 3+ years’ programming skills experience (e.g. Bash, R, Python) and bioinformatic tools (bcftools) and workflow management systems (e.g. nextflow).
3. 3+ years’ experience in processing and analysis of large-scale genomic datasets, (genetic data analysis including SNVs/CNVs, WES/WGS required), and data interpretation through integration with clinical/phenotypic information.
4. 3+ years’ experience in cancer research, including a deep understanding of computational approaches for cancer genome analysis.

Preferred Qualifications:

1. Proven ability to effectively lead multidisciplinary teams to answer complex scientific questions.
2. Evidence of independence in leading research projects and of the ability to develop novel statistical or bioinformatical methods.
3. Advantageous to have experience in complex molecular data integration, such as transcriptomics, proteomics, and metabolomics.
4. Strong communication skills to convey complex ideas and concepts to a range of stakeholders.
5. Excellent problem-solving and analytical skills to address complex scientific questions.
6. Strong collaboration and partnership skills to work effectively with cross-functional teams.
7. Excellent project management skills with a focus on delivering results.

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