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Department of Ruminant Science
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| Using computer vision and deep learning networks to quantify various behaviors of dairy cattle |
Our research uses image collection to measure eating behavior and social interaction of dairy cattle: calves, heifers, and lactating cows. We use convolutional neural networks (CNN) to classify individual eating behavior and characterize social interactions. During the project, we collected and cured extensive data set for training of CNN’s models capable of classification and segmentation of cattle in their commercial environment
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| Education requirements |
| Ph.D. in the fields of animal, natural, agricultural, or computer science |
| Scientific experience |
| The candidate must have proven (published works) experience in large data processing, scientific writing, and mathematical or statistical modeling. The candidate must have experience using R, Python, MatLab, or other appropriate tools. |
| Skills |
| The following abilities and skills are to be considered when evaluating applications: algorithmic coding, image processing, computer vision, deep learning, teamwork, and experiments designing and concluding. |
Poultry and Aquaculture
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| Response and adaptation of tilapia to environmental stress |
We study the genetics and physiology of tilapia response and tolerance to temperature and salinity stress. We use high throughput genomic analyses, in vivo and in vitro molecular techniques, metabolic chambers, imaging and behavioral analyses, to study the whole animal and tissues response and the central regulation by neuroendocrine pathways.
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| Education requirements |
| Ph.D. |
| Scientific experience |
| Preferred experience in molecular biology or bioinformatic or physiological experiments. |
| Skills |
| Curiosity, high motivation, independence |
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| Updated on: 18/05/22 20:04 |
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