Sort by
Refine Your Search
-
equitable access to health apps, including through standardized quality labels displayed in app stores. The position offers the opportunity to conduct research with direct practical relevance, collaborate
-
Is the Job related to staff position within a Research Infrastructure? No Offer Description Be part of a major European initiative to make safe, trustworthy health apps accessible to everyone. As part
-
, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our
-
neurobiology, biochemistry, genetics, and proteomics. Expertise in APEX/BioID-based proximity labelling, biochemistry, proteomics is required Experience in mice handling and behaviour, microscopy, AI protein
-
interactions. Applicants must also have some experience in working with omics data, with previous experience in proximity-labelling-based proteomics being a strong merit. Candidates should be passionate about
-
and interpersonal skills, with the ability to work effectively, both independently and as part of a team, Willingness to learn new methods and develop interdisciplinary research. For this position you
-
participants, Excellent communication skills in English and Finnish, both spoken and written. Strong organizational and interpersonal skills, with the ability to work effectively, both independently and as part
-
under climate change? This fully funded 2-year postdoc project is part of a research program funded by the Swedish Research Council (Vetenskapsrådet) on the vulnerability of fish life stages to climate
-
at the University of Turku and is part of the Research Council of Finland Flagship Programme InFLAMES . Job description We are seeking a highly motivated postdoctoral researcher to study the regulation of immune
-
seeking a highly motivated Postdoctoral Researcher to join the Machine Learning cluster. The position is part of a research project investigating how visual foundation models can efficiently acquire new