Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
positions) / a PhD (Postdoc positions) in natural sciences (i.e. Chemistry, Physics, or Materials Science) preferably with a specialization in theoretical chemistry, or applied mathematics An appropriate
-
learning or applied mathematics. Required skills and qualities: - Fluency with Python programming for data analysis or machine learning, - Knowledge of statistical or probabilistic modelling techniques
-
; representation from three continents). Our lab’s strength lies in integrating multiple disciplines: Single-cell microfluidics Quantitative (image) analysis Mathematical modelling Microbiology Molecular biology We
-
spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025, and will remain open until excellent fits are found.The
-
modelling the coupling of atmospheric and micro-physics moisture dynamics. The work will be carried out in collaboration with and under the supervision of Professor Edriss S. Titi. Duties include mathematical
-
successful candidate will have previous experience in computer science or data science, with a PhD and publications in at least one of the following areas: Formal modelling and verification of business
-
Postdoc in modelling Greenland and Himalaya precipitation using machine learning Faculty: Faculty of Science Department: Department of Physics Hours per week: 36 to 40 Application deadline: 26
-
Job description We are recruiting postdocs to contribute to research projects in the Mathematical Modelling of Infectious Diseases Unit, at Institut Pasteur in Paris. The candidates will be expected
-
. To address these questions, we combine a series of interdisciplinary approaches ranging from experimental embryology and fluorescent microscopy to mathematical modelling. The lab is highly interdisciplinary
-
, is seeking highly motivated candidates for multiple postdoctoral positions. We are specifically looking for candidates who possess a strong background in theoretical and computational modeling