Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Job description The Affinity Proteomics unit (https://www.scilifelab.se/facilities/affinity-proteomics/ ) is part of
-
Referensnummer REF 2026-0054 Chalmers University of Technology is host for a well-funded tenure-track Assistant Professor position in Data Driven Cell and Molecular Biology, in a vibrant
-
developing and implementing data management for human data to meet future needs within data-driven Life Science research. More information about NBIS can be found at https://nbis.se . Duties We are looking
-
methods for analysis of cellular and molecular biology data. The host institution, The Department of Gene Technology , is the most prominent research environment at KTH, according to bibliometrics
-
A position as Associate Senior Lecturer/Assistant Professor (tenure track) within the area Data-Driven Evolution and Biodiversity in aquatic or terrestrial environments is open at the Swedish
-
Uppsala University, Department of Cell and Molecular Biology Do you want to work on enabling groundbreaking, data-driven Life Science research in an international environment, supported by competent
-
program Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes
-
spectrometry imaging (MSI) of brain tissue. The missingness can happen along two dimensions: spatial (super resolution) and feature (data imputation). Enhancing the quality of MSI advances our understanding
-
university. More information about us, please visit: the Department of Biochemistry and Biophysics . Project description Project title: Perturbation-based Multi-omics Inference of Gene Regulatory Networks
-
). The project focuses on developing computational models for cancer risk assessment, integrating multiple types of data and risk factors. The main objective is to design and apply machine learning and deep