Sort by
Refine Your Search
-
. The candidate will combine experimental and computational approaches. The project will start with bioinformatics-driven analysis, followed by integration of data generated from experimental models. Over time, the
-
. The project explores the role of tumor-promoting inflammation in cancer progression through bioinformatics-driven, machine-learning and multi-omics analyses integrated with experimental data. Ideal candidates
-
part of an ERC starting grant and involves studying the impact of disease on endosomal properties and the processing of lipid nanoparticles. Key techniques will include omics, cell culture and small
-
relevant to the subject area. In the appointment process, special attention will be given to research skills. We are looking for candidates with wet-lab expertise in RNA biology and next-generation
-
of organisms, and how these processes respond to environmental changes. Recent advancements in plant and animal physiology have been accelerated by the use of novel single-cell and tissue analysis techniques
-
substantially equivalent knowledge in some other way. For this position, the applicant must hold a master’s degree in molecular biotechnology, bioinformatics, computer science, or another area that the employer
-
efficiently interact in the interdisciplinary project. We seek candidates with a strong computer science, mathematics, statistics, or bioinformatics background and strong programming skills. Some previous
-
(DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global
-
computational and statistical methods, with demonstrated experience in reproducible and scalable bioinformatics environments. The applicant will work in close collaboration with other Engblom lab team members who
-
variability in risk factor susceptibility, treatment response, disease pathogenesis, and clinical diagnosis (biostatistics, machine/deep learning), ii) Investigating causal processes and disease mechanisms