Build, Train and Test multiple CNN models.
Optimizing model training & inference by utilizing multiple GPUs and CPU cores.
Keen interest in Life Sciences, Image processing, Genomics, Multi-omics analysis
Interested in reading and implementing research papers of relevant field.
Strong experience of Deep Learning frameworks TensorFlow, Keras, PyTorch.
Strong programming skills in python and experience of Ski-Learn/NumPy libraries.
Experience of training of Object detection Models like YOLOv3/Mask CNN and semantic segmentation models like DeepLab, Unet etc.
Good understanding of image processing and computer vision algorithm like watershed, histogram matching etc.
Experience of cell segmentation and membrane segmentation using CNNs (Optional)
Individual Contributor

Desired Candidate Profile

Minimum qualification B.E/B.Tech. in Computer science or equivalent stream.

Must have:

Experience with image processing
Experience required : 2-10 Years
CTC :15-40 LPA
Good python programming and algorithmic skill.
Experience with deep learning model training using any known framework.
Working knowledge of the genomics data in R&D

Preferred

Understanding of one or more omics data types (transcriptomics, metabolomics, proteomics, genomics, epigenomics etc.)
Prior work experience as a data scientist, bioinformatician or computational biologist will be a big plus

Roles and Responsibilities

Build, Train and Test multiple CNN models.
Optimizing model training & inference by utilizing multiple GPUs and CPU cores.
Keen interest in Life Sciences, Image processing, Genomics, Multi-omics analysis
Interested in reading and implementing research papers of relevant field.
Strong experience of Deep Learning frameworks TensorFlow, Keras, PyTorch.
Strong programming skills in python and experience of Ski-Learn/NumPy libraries.
Experience of training of Object detection Models like YOLOv3/Mask CNN and semantic segmentation models like DeepLab, Unet etc.
Good understanding of image processing and computer vision algorithm like watershed, histogram matching etc.
Experience of cell segmentation and membrane segmentation using CNNs (Optional)
Individual Contributor

Desired Candidate Profile

Minimum qualification B.E/B.Tech. in Computer science or equivalent stream.

Must have:

Experience with image processing
Experience required : 2-10 Years
CTC :15-40 LPA
Good python programming and algorithmic skill.
Experience with deep learning model training using any known framework.
Working knowledge of the genomics data in R&D

Preferred

Understanding of one or more omics data types (transcriptomics, metabolomics, proteomics, genomics, epigenomics etc.)
Prior work experience as a data scientist, bioinformatician or computational biologist will be a big plus

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Full Stack Developer - Averlon

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About Applied Materials

Founded

Type

Size

Stage

About

Applied Materials is the leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. Our expertise in modifying materials at atomic levels and on an industrial scale enables customers to transform possibilities into reality. At Applied Materials, our innovations Make Possible a Better Future.

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