Postdoc in Computational Biology of Human Tissue Architecture Full-time

Postdoc in Computational Biology of Human Tissue Architecture

Tissue organization is achieved by the genome encoding both cell type identity and extracellular signaling, but how cell types, signaling mechanisms, and transcription factors jointly determine tissue structure is incompletely understood. The Koplev lab is recruiting an outstanding and ambitious postdoctoral researcher in computational biology to pioneer understanding and modeling of tissue architecture using single-cell and spatial transcriptomics data. The focus will be on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and gastrointestinal tract. The research will establish spatiotemporal models of human tissue architectures, revealing how niches form, change, and malfunction across human organs and diseases. This may include investigating tertiary lymphoid structures in inflammatory diseases, interorgan endocrine signaling, the comparative niches of stem cells across tissues, or mechanisms of transcriptional regulation such as alternative splicing, depending on the interests and expertise of the applicant.

The successful candidate will join a growing collaborative research group, who works closely with researchers in the Department of Gene Technology, SciLifeLab, as well as leading international research groups. The job involves developing and executing primary research projects in computational biology, leading to dissemination and publication in academic journals and conferences. Moreover, the role will support and provide key operational contributions to scientific excellence and productivity of the research lab, assisting in shaping and directing students achieve individual and collective research goals. This provides opportunities for training in scientific leadership for eventual application as an independent group leader or senior staff scientist.

Qualifications

Requirements

• A doctoral degree or an equivalent foreign degree. This eligibility requirement must be met no later than the time the employment decision is made.
• Substantial research expertise in computational biology methods for single-cell or spatial transcriptomics data.
• Proven scientific excellence as evidenced by strong scientific publications and track record relative to career stage.
• Strong programming skills (Python or R) and familiarity with high-performance computing

Preferred qualifications

• A doctoral degree or an equivalent foreign degree, obtained within the last three years prior to the application deadline
• Highly creative researcher with broad scientific curiosity
• Mastery of data visualization and scientific communication
• Extensive knowledge of relevant machine learning and AI techniques
• Exceptional collaborative abilities
• Self-motivated individual with ability to work independently
• Teaching and mentorship abilities or interests in personal development
• Awareness of diversity and equal opportunity issues, with specific focus on gender equality

We welcome applicants from diverse backgrounds and with complementary strengths.

Great emphasis will be placed on personal skills.