Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
organization skills. Experienced in workflow design and technical documentation. PREFERRED QUALIFICATIONS Experience developing AI methods for environmental data sets including working with deep learning
-
. Preferred: • Strong programming skills in languages such as R/Python • Research background in biostatistics/statistical genetics/population genetics/deep learning and LLM • Experience in any of the following
-
bioinformatics methods have made significant strides, AI approaches - particularly deep learning - are revealing patterns and relationships in biological data that were previously inaccessible. As a postdoctoral
-
with deep learning libraries (e.g., PyTorch) Ability to organise and prioritise work to meet deadlines with minimal supervision Strong written and verbal communication skills, with the ability to convey
-
About Mohammed VI Polytechnic University (UM6P) Mohammed VI Polytechnic University (UM6P) is an internationally oriented institution of higher learning, that is committed to an educational system
-
/C++; hands-on experience with deep learning libraries (e.g., PyTorch) 5. Ability to organise and prioritise work to meet deadlines with minimal supervision 6. Strong written and verbal
-
on histopathology image data. As a postdoctoral researcher you will be involved with development and validation of AI/deep learning solutions for precision medicine and patient stratification (patient outcome
-
, and deep learning. A Ph.D. in Statistics, Mathematics, CS/EE (with a focus on statistics/machine learning) or a directly related field at the time of appointment is required. The successful applicant
-
models (e.g. mixed-effects regressions, Bayesian analyses). You preferably have experience supervising and/or teaching students. You preferably have knowledge of swarm robotics and/or deep learning
-
and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning