Sort by
Refine Your Search
-
landmark database on university deep tech startups, carry out independent, high-quality research leveraging this data, and engage with stakeholders in the Danish and international deep tech arena
-
interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer
-
analyses of large amounts of data generated within biological, biomedical and biotechnological and life sciences area. We strive to gain new knowledge and drive innovation in human, animal, plant and food
-
people and creating value for society. The department has a scientific staff of about 210 persons, 140 PhD Students, and a technical/administrative support staff of about 100 persons of which a large