I'm qualified and responsible doctoral researcher and data scientist, My experience,particularly with a Leap Conseil (Montreal) as Data Science Advisor, Lead Data Scientist at DNA Global Analytic(Geneva) and Through my experience as Chef Projects at iConnetServices(Tunis), Applied experience in a field with very large and complex data sets such as Biology, Physics, or Social Sciences. PhD Position in Deep Learning Medical imaging for Diabetic Retinopathy classification... Experience with sensor data standards and sensor systems is desired ,Experience in software development and agile methodologies for delivering analytics outcome  5 years of experience in at least one of the following Supervised and Unsupervised Learning, Classification Models, Cluster Analysis, Neural Networks, Non-parametric Methods, Multivariate Statistics, Reliability Models, Markov Models,Stochastic models, Bayesian Models Assess and approve documents for contribution to the corpus upon which NLP.

Engineering Experiences Fileds : 

• Image Processing algorithms e.g.

  • Segmentation, Filter Design, Noise Reduction, Compression, Image Fusion, Super-Resolution.

• Computer Vision algorithms e.g.

  • Target Acquisition, Tracking, Optical Flow, Kalman Filtering, Pose Estimation.

• Computational Imaging e.g.

  • Compressive Sensing, Synthetic Aperture Radar, Doppler Beam Sharpening.

• Deep Learning e.g.

  • Classification, Detection, Siamese Networks, Residual Learning, Deep Embeddings, Recurrent Networks.

• Machine Learning for classification and regression problems e.g.

  • Support Vector Machines, Probabilistic Models, Neural Networks.

• Domain Specific Signal Processing e.g.

  • Multi/Hyper-Spectral, RF, IR, SAR

 knowledge and experience in:

• Matlab, Simulink and/or Stateflow

• Python including PyTorch, TensorFlow, OpenCV

• Model Based Design