-
on Quadruplex DNA structures. The fellowship is expected to start in 2025-08-15 or according to agreement. Application deadline is May 5th, 2025. Description of the project In addition to the classical double
-
interested in using and developing state-of-the-art methods in biophysics and structural biology (e.g. RNA probing & SHAPE, or NMR). Are you looking for an employer that invests in sustainable employee ship
-
to study biological systems and processes at all levels, from molecular structures and cellular processes to human health and global ecosystems. The SciLifeLab and Wallenberg National Program for Data-Driven
-
of adaptive radiation. You will explore questions such as: How does ecological opportunity and niche-structural components of relevance for ecological diversification and speciation affect the way adaptive
-
KTH Royal Institute of Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health Job description Professor Tuuli Lappalainen’s research group is looking for a researcher for
-
, SciLifeLab is located on Campus Solna, where research groups from Stockholm University, the Royal Institute of Technology, and the Karolinska Institute conduct internationally outstanding research in the life
-
of Technology (MIT), and Chalmers Institute of Technology. Your mission You will design and analyze a high-throughput stimulus-response experiment in cancer and stroma cells that will be conducted at our core
-
-of-the-art cell and tumor biology methodologies, tissue analysis with histopathological techniques, and work with genetically engineered mouse models of cancer. Previous experience of conducting and analyzing
-
, entrepreneurship and leadership training, to develop expertise to address related challenges. Technology and methodology skills: Research methodology and technology training, according to an individually designed
-
our work. Project 2: Further development and use of our in-house pipeline for large-scale mechanistic model construction to train personalized computational models for studying in-silico clinical