Data Analysis ofertas em Emirados Árabes Unidos

Responsibilities

• Lead bioinformatics projects to address key biological questions, uncover novel insights and generate novel data-driven hypotheses.
• Develop, implement, and optimize computational pipelines to process and analyse large-scale transcriptomic datasets, with a focus on single-cell and spatial ‘Omics’ data.
• Show increased ability to work independently and collaborate cross-functionally with wet lab scientists, providing bioinformatics expertise to design experiments, interpret data and validate results.
• Plan and prioritize tasks to ensure timely delivery of results delivery for key experiments
• Develop in-depth knowledge in selected biological disciplines, enabling the extraction of meaningful biological insights form complex datasets and interpretation of results.
• Lead new initiatives and research projects and contribute to publications.

Job Requirements

• PhD in computational biology or related disciplines
• A demonstrated expertise with single-cell genomics data, including hands-on experience with scRNA-seq and/or other single-cell modalities; experience with spatial transcriptomics is a strong advantage.
• Knowledge and experience in analysing and integrating multiple omics data types (e.g. genomics, transcriptomics, epigenomics, proteomics)
• Excellent programming and data science skills with proficiency in R and Python.
• A solid understanding of human biology, including cell/molecular/disease biology.
• Strong foundation in statistics and application of machine learning techniques to biological datasets.
• Proficiency with structuring projects and code for robust, generalizable, and reproducible data analysis.
• Advanced data visualization skills, with the ability to communicate complex findings effectively.
• Excellent communication and presentation skills with the ability to convey complex ideas clearly.
• Strong team-oriented mindset and interpersonal skills. You contribute to a diverse, open, and collaborative working environment, and prioritize knowledge sharing.