AGBS - Postdoctoral position in High Throughput Phenotyping and Plant Stress Resistance

AGBS - Postdoctoral position in High Throughput Phenotyping and Plant Stress Resistance

Mohammed VI Polytechnic University is an institution oriented towards applied research and innovation with a focus on Africa.

Position Announcement - Mohammed VI Polytechnic University (UM6P), College of Sustainable Agriculture and Environmental Science (CSAES), AgroBioSciences program (AgBS).

Job Title – Post-Doctoral Fellow in bioinformatics data analysis and mining

Duration: 3 years

Keywords: Computer science, Bioinformatics, Data science, Big Data, Machine learning, Deep learning

About UM6P: Mohammed VI Polytechnic University (UM6P) is an international higher education institution, established to provide research and innovation at the service of education and development for Morocco and the African continent. It has a state-of-the-art campus at the heart of the Green City of Benguerir, near Marrakesh. UM6P academics and staff enjoy strong research funding, moderate teaching loads, and excellent facilities.

About the College of Sustainable Agriculture and Environmental Science (CSAES) and AgroBiosciences Program (AgBS) at UM6P: The CSAES constitutes a structure of higher education and practical-based research with a vision of solving real African agriculture challenges leveraging up-to-date science and technology.

About the PHENO-MA Platform: The PHENO-MA is an innovative research platform for high-throughput plant phenotyping built and established at UM6P in Benguerir, Morocco. It can be used to assess plant responses to nutrient deficiency, drought, high temperature, pests, and diseases.

We are seeking applications for a Post-Doctoral Fellow in bioinformatics data analysis and mining to support the implementation and improvement of PHENO-MA phenotyping platform. The successful candidate will be responsible for working with a multidisciplinary team of researchers and engineers to design and develop data-driven and AI-driven solutions to help farmers improve crop yield.

Main responsibilities:

1. Work closely with a multidisciplinary team to develop and implement data-driven and AI-driven solutions based on collected data.
2. Provide application support to projects through benchmarking, code optimization, and scalability of applications.
3. Collect and analyze data from various sources to develop predictive models and decision support tools.
4. Perform cutting-edge research tasks in deep learning-based crop yield prediction and genomic prediction.
5. Contribute to the development and implementation of a data management and quality control infrastructure.
6. Conduct exploratory analyses for trait discovery and genetic diversity assessment.
7. Develop and implement data visualization tools.
8. Continuously evaluate the latest packages and frameworks in the ML ecosystem.

Required qualifications:

1. PhD degree in Computer Science, Bioinformatics, Machine Learning, or equivalent.
2. Advanced knowledge in Data engineering, Machine Learning, and Deep Learning.
3. Experience in a research environment with a good track record.
4. Proficiency in Python, SQL, and ML/DL frameworks such as Tensorflow and PyTorch.
5. Experience with exploratory data analysis and statistical analysis.
6. Understanding of project management best practices.
7. Good English communication skills.

Preferred qualifications:

1. Prior exposure to MLOps/DataOps processes.
2. Academic experience in crop improvement or related fields.
3. Experience with deep multimodal learning and computer vision.

Employment terms: The successful candidate will be employed on a competitive salary by Mohammed VI Polytechnic University (UM6P) based in Benguerir, Morocco.

Applications and selection procedure: Applications must be sent using a single electronic zipped folder with the mention of the job title in the email subject. The folder must contain a cover letter, detailed CV, and contact information of 3 references.

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