Sort by
Refine Your Search
-
Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
of Magnetic Resonance Imaging (MRI). Building on the various contrasts mechanisms available in multi-parametric MRI, we aim to establish deep learning models that predict biomarkers of diseases progression and
-
computational (deep-learning AI models) approaches to dissect cell-death signaling, with ultimate goals to identify novel therapeutic targets and approaches. The PI, Dr. Gong has been highly regarded in his
-
to explore new analysis methods using deep learning. Depending on the interest, it is also possible to be involved in the wet lab. Professor Tiwari also leads the Center for Integrated Multiomics in Precision
-
strong background in image processing and analysis, including deep learning (e.g., CNNs) experience with correlative imaging workflows and 2D/3D registration techniques strong programming skills in Python
-
for image-based modelling Your profile PhD in physics, materials science, computer science, applied mathematics or a related field strong background in image processing and analysis, including deep learning
-
Science, Computer Engineering, Artificial Intelligence, Physics, Mathematical Engineering, Mechanical Engineering or similar. Relevant skills: Strong background in machine learning/data science. Deep knowledge
-
cutting-edge technologies — from single-cell multi-omics and deep learning to live-cell imaging and stem-cell–based organoid systems — to predict, observe, and manipulate epigenetic processes. Our lab and
-
(or near completion) in computer science, machine learning, statistics/biostatistics, computational biology, data science, physics, or a related field. Experience with modern deep learningframeworks (e.g
-
into global environmental changes, and ecosystem sustainability Experience with deep learning, radiative transfer modeling Teaching and supervision experience Who we are At the Department of Agroecology, our
-
/ Deep Learning (particularly Computer Vision or 3D perception) Verification & Validation (V&V) of advanced algorithms, software or systems Formal Methods Safety Engineering / Safety-Critical Systems