28 web-programmer-developer-"INSERM" research jobs at UNIVERSITY OF HELSINKI in Finland
Sort by
Refine Your Search
-
using unique novel mouse models, spatial technologies and analytical methods. Postdoctoral Researcher in Functional Cancer Microbiome through the NORPOD program NORPOD is a collaborative postdoctoral
-
-Cell Genomics through the NORPOD program NORPOD is a collaborative postdoctoral program of the Nordic EMBL Partnership for Molecular Medicine . The partnership is a network of four national research
-
& al. 2022, PMID: 35164752,Gondane & al. 2023, PMID: 36975490, and Liang & al. 2024, PMID: 38775167). For further information, please refer to our research groups’ web pages: https://www.helsinki.fi/en
-
at the Faculty of Medicine, University of Helsinki. The project will focus on using and extending deep learning-based approaches developed within the group to integrate bulk multi-omics cancer data. The Kuijjer
-
Cancer Medicine at the Faculty of Medicine, University of Helsinki. The project will focus on developing approaches for gene regulatory network modeling on deconvoluted bulk data, with applications to pan
-
will work within the research project “Structural correctness in metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop
-
. We will develop an isotope version of a process-based CH4 model and update the representation of different wetland types in the model using a data inversion approach. Additionally, we will analyze
-
metagenomics assembly” funded by the Research Council of Finland in the research group of University Lecturer Leena Salmela. We develop models, algorithms and data structures for high throughput sequencing data
-
medication security are challenged by the high costs of development, manufacture and distribution, evaluation of preclinical safety and efficacy, and the dependence of drug manufacturing on international
-
, calibration, and the development of analysis tools and software. Our key focus areas are the physics of jets, top quarks, and EWSB, including the development of novel machine-learning methods for high-energy