Sort by
Refine Your Search
-
Listed
-
Program
-
Field
-
analysis and multi-omics data integration workflows using Python/R Integrate digital pathology data with omics data (e.g., MS-based proteomics, spatial proteomics) Develop and drive independent project ideas
-
Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
., using FEniCSx) Advanced knowledge of scientific programming, preferably in Python, including experience with implementing machine‑learning methods (e.g., PyTorch) Excellent spoken and written English, as
-
) Experience in cellular and molecular biology, including histology and cell culture (required) Familiarity with using R and/or Python for answering biological questions (required) An enthusiastic and friendly
-
Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
-
datasets Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl, C++, R) Well-developed collaborative skills We offer The successful candidates will
-
and Python programming skills are an advantage. Passionate about science communication and cultivating collaborative relationships with industry professionals. Excellent written and spoken English. A
-
someone who wants ownership, visibility, and scientific freedom. Your Profile PhD in molecular biology, bioinformatics, marine biology, or a related field Strong skills in R and/or Python and
-
, or biophysical simulations. Demonstrated interest in biological systems, prior experience in biological modeling and in transcriptomic data analysis. Proficiency in programming (e.g., Python, R) and familiarity
-
for engineers Good knowledge of experimental techniques and control engineering Strong programming skills, particularly in Python and Fortran 90 Knowledge of fracture mechanics is an asset Excellent command
-
, systems biology, biomedical data science, cancer biology, or a related field Strong experience in omics data analysis, ideally including single-cell or spatial transcriptomics Proficiency in R and/or Python