Tenure-Track: Rapid Marine Adaptation & Evolutionary Genomics

Univie; Wien; Hybrid; EUR 85.000 - 105.000; Vollzeit

Zusammenfassung

The University of Vienna invites applications for a Tenure Track Professorship in Rapid Marine Adaptation. We seek a scientist with an outstanding record in marine evolutionary genomics investigating rapid evolutionary responses through field studies and/or experimental evolution.

Collaborations with physiologists, ecologists, biochemists and systems biologists in Vienna will link genomic targets of selection to organismal phenotypes and local environmental conditions, advancing predictive

Qualifikationen

• Two years international research experience during or after doctoral studies.
• Outstanding research achievements with publications and funding records; international reputation.
• Gender and diversity competence.
• Experience designing and participating in research projects; ability to lead groups and obtain funding.
• Enthusiasm for teaching and supervision at bachelor, master and PhD levels.

Aufgaben

• Conduct research in rapid marine adaptation, focusing on evolutionary genomics and predictive modeling.
• Lead and manage interdisciplinary research projects and collaborations.
• Publish in high-impact journals and secure external funding.
• Teach and supervise students across undergraduate to doctoral programs.

Kenntnisse

International research experience

Marine evolutionary genomics

Teaching and supervision

Grant writing

Interdisciplinary collaboration

Ausbildung

PhD in marine biology/genomics

Tools

Genomic sequencing

Jobbeschreibung

The University of Vienna invites applications for a Tenure Track Professorship in Rapid Marine Adaptation. We seek a scientist with an outstanding record in marine evolutionary genomics investigating rapid evolutionary responses through field studies and/or experimental evolution.

Collaborations with physiologists, ecologists, biochemists and systems biologists in Vienna will link genomic targets of selection to organismal phenotypes and local environmental conditions, advancing predictive