38 algorithm-development "https:" "Simons Foundation" Postgraduate positions in Germany
Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
Infrastructure? No Offer Description Work group: IBG-4 - Bioinformatik Area of research: PHD Thesis Job description: Your Job: Chromatography modeling, while crucial for modern bipporcess development, still
-
Infrastructure? No Offer Description Work group: IBG-4 - Bioinformatik Area of research: PHD Thesis Job description: Your Job: Develop methods and workflows to construct robust co-regulation networks from large
-
Infrastructure? No Offer Description Work group: JSC - Jülich Supercomputing Centre Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student to develop learning-based surrogate
-
Infrastructure? No Offer Description Work group: JSC - Jülich Supercomputing Centre Area of research: PHD Thesis Job description: Your Job: We are looking for a PhD student to contribute to the development of fast
-
a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop 3D+t image reconstruction methods in a cell microscopy setting using image sequences
-
retreats) https://www.hds-lee.de/about/ A qualification that is highly welcome in industry 30 days of annual leave and flexible working arrangements, including partial remote work Further development of your
-
interdisciplinary team Motivation for academic development, supported by bachelor’s and master’s transcripts and two reference letters Working proficiency in English for daily communication and professional contexts
-
Your Job: This PhD project bridges between classical analytical methods and modern AI based techniques to analyse spike train recordings to advance our understanding of neural population coding
-
data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in industry Further development of your personal strengths, e.g. via a
-
models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools