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1. Position Announcement: PhD student position

Job Title: Perceptions on Yield and Precipitation Gaps, and Crop Calendars for Cereals in Morocco

Area of specialization in IWRI: Climate Change Impacts on Agriculture and development

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Job description:

We are seeking a PhD candidate for the above thesis. The focus of this work will be to assess farmers’ perceptions of crop yield and precipitation gaps in the Tensift Basin of Morocco and possibly other basins, where cereals are cultivated. Activities include identifying farmers’ perceptions about their past, current, and future yields and precipitation levels, and their views with respect to options for closing yield gaps such as water management and nutrient level changes. This will also involve an evaluation on the relationship between respondents’ perceptions on yield and precipitation gaps and their socio-demographics characteristics. This primary data can be culled through questionnaires, interviews, and group discussions. The ideal candidate for this work should have experience with drafting and administering questionnaires, managing group discussions and interviews, as well as in advanced statistical models to analyze the collected data.

Key duties:

The key deliverables will include:

1) A systematic review identifying the current research gaps in this area of research.

2) Drafting, designing and administration of questionnaires and surveys.

3) Organization of data collection on farmers’ characteristics and their perceptions (on yield and precipitation gaps) , including sampling and administrative steps.

4) Reports and draft articles on data collections and econometric analysis to derive the drivers of farmers beliefs on yield and precipitation gaps in Tensift Basin.

5) Crop calendars elaboration in Tensift Basin

6) Adoption and sociodemographic of nutrient and water management options as strategies for closing yield and precipitation gaps

Criteria of the candidate:

The ideal candidate should:

  1. Have a master’s degree in geography, rural engineering, agriculture or agronomy, social sciences, or a related discipline.

  2. A publication record is an asset

  3. Show ability and willingness to draft, design and, administer survey, questionnaires, and analyze collected data

  4. Excellent Excel skills and practical knowledge of at least two of the following data analyses software: SPSS, R, python.

  5. Experience in collecting data and managing survey data would be a strong asset.

  6. An understanding of crop calendars for cereal crops is important.

Candidates should be particularly motivated and interested in the impacts of climate change on arid food systems. Candidates who have proven experience in the design, administering and analyses of questionnaires, focus group discussions, key informant interviews will be given priority. Candidates with experience in the use of at least two software such as SPSS, excel and others will be given priority. The ideal candidate should have a strong understanding and ability to use systematic reviewing techniques. Candidates with publication records and the ability to take initiative, work independently, develop, and design their own proposals as well as work in groups will be given priority.

Applications:

Applications must include the following: 1) a cover letter 2) a detailed Curriculum Vita, 3) CERTIFIED copies of all transcripts at bachelors and masters or equivalent, 4) Electronic copies of the Master thesis, 5) Cover letter 6) Letter of motivation, 7) Research proposal of two pages maximum and 8) Two letters of reference.

For any enquiry, please contact PAMOCPP PI: Prof. Dr. Terence Epule Epule (epule.terence@um6p.ma), WP3 lead: Prof. Dr. Tarik Chfadi (tarik.chfadi@um6p.ma) and the program lead of IWRI: Prof. Abdelghani Chehbouni (abdelghani.chehbouni@um6p.ma)

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2. Position Announcement: PhD Student Position

Job Title: Closing Yield Gaps via Nutrient and Water Management for Maize, Barley, Sorghum and Beans at a National Scale in Morocco

Area of specialization in IWRI: Climate Change Impacts on Agriculture

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Job description:

We are in search for a PhD student to work on the above topic and in collaboration with a team of researchers and a PDF. The focus of this fellowship will be to identify ways of closing yield and precipitation gaps through nutrient and water management options. Evaluating opportunities for more sustainable intensification requires an understanding of the factors driving yield variations across Morocco. Yield gaps are often driven by deficiencies in the biophysical crop growth environment that are not addressed by agricultural management options. It becomes important to explicitly examine the most important biophysical drivers of crop yield by using crop-specific irrigation data and develop a new Moroccan, crop-specific data set of nitrogen (N), phosphate (P2O5) and potash (K2O) fertilizer application rates. By using non-linear regression analyses, within each climate zone, data on irrigation and fertilizer usage can be used to parameterise nutrient and water management maximum yield. These relationships can be used to estimate changes in inputs required to close the observed gaps as well as declines in the inputs needed to address inefficiencies and imbalances.

Key duties:

The key deliverables will include:

  1. To conduct systematic reviews to identify the current research gaps in this area of research.

  2. Using appropriate empirical modelling and process-based modelling approaches to close yield and precipitation gaps.

  3. Identify the drivers of Yield and Precipitation Gaps (Biophysical and Non-biophysical)

  4. Closing Yield and Precipitation Gaps through nutrient and water management

  5. Analysing the drivers of fertilizers and irrigation schemes

  6. Assess the level of adoption of various water and nutrient management options using adoption models in closing yield and precipitation gaps.

Criteria of the candidate:

The ideal candidate should:

  1. Must have completed a master’s degree in geography, agronomy, agrometeorology, agriculture, water, and resource management, and environmental sciences or a related discipline.

  2. An emerging publication record is an asset but not an obligation.

  3. Strong statistical analysis; empirical and process-based modeling through any appropriate models and models like AQUACROP, WABAL, EPIC, DDSAT, APSIM, and SPSS, etc.

  4. Capable of using at least two of the following programming skills: R, Python, Matlab.

  5. Knowledge of nutrient and water management repositories.

Candidates should be particularly motivated by and interested in the impacts of climate change on arid food systems and on how nutrient and water management can be used to fix gaps. Proven experience and skills in the use of process-based models in assessing crop response to environmental conditions is at the core. Candidates must have experience in the use of software such as Python, R Programming, SPSS, among others. The ideal candidate should have a strong understanding and ability to use systematic reviewing techniques. Publication record and the ability to take initiative, work independently, develop, and design their own proposals as well as teamwork are an added advantage.

Applications:

Applications must include the following: 1) a cover letter 2) a detailed Curriculum Vitae, 3) Certified copies of all transcripts at bachelors, masters, and PhD or equivalent, 4) Electronic copy of the PhD thesis 5) Two relevant publications 6) Letter of motivation, 7) Research proposal of three pages maximum and 8) Two reference letters.

Deadline for applications: 30th June 2022.

For any enquiry and applications, please contact PAMOCPP PI: Prof. Dr. Terence Epule Epule (epule.terence@um6p.ma), WP4 Lead: Prof. Dr. Victor Ongoma (victor.ongona@um6p.ma) and the program lead of IWRI Prof. Dr. Abdelghani Chehbouni (Abdelghani.chehbouni@um6p.ma).

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3. Position Announcement: Post-Doctoral Fellowship

Job Title: Closing Yield Gaps via Nutrient and Water Management for Maize, Barley, Sorghum and Beans at a National Scale in Morocco

Area of specialization in IWRI: Climate Change Impacts on Agriculture

Job description:

We are in search for a two-year term (possibilities for extension) post-doctoral fellow to work on the above topic. The focus of this fellowship will be to identify ways of closing yield and precipitation gaps through nutrient and water management options. Evaluating opportunities for more sustainable intensification requires an understanding of the factors driving yield variations across Morocco. Yield gaps are often driven by deficiencies in the biophysical crop growth environment that are not addressed by agricultural management options. It becomes important to explicitly examine the most important biophysical drivers of crop yield by using crop-specific irrigation data and develop a new Moroccan, crop-specific data set of nitrogen (N), phosphate (P2O5) and potash (K2O) fertilizer application rates. By using non-linear regression analyses, within each climate zone, data on irrigation and fertilizer usage can be used to parametrize nutrient and water management maximum yield. These relationships can be used to estimate changes in inputs required to close the observed gaps as well as declines in the inputs needed to address inefficiencies and imbalances.

Key duties:

The key deliverables will include:

  1. To conduct systematic reviews to identify the current research gaps in this area of research.

  2. Using non-linear regression and other process-based model approaches to close yield and precipitation gaps.

  3. Identify the drivers of Yield and Precipitation Gaps (Biophysical and Non-biophysical)

  4. Closing Yield and Precipitation Gaps through nutrient and water management

  5. Analysing the drivers of fertilizers and irrigation schemes

  6. Assess the level of adoption of various water and nutrient management options using adoption models in closing yield and precipitation gaps.

Criteria of the candidate:

The ideal candidate should:

  1. Must have completed a PhD degree in geography, agronomy, agrometeorology, agriculture, water, and resource management, and environmental sciences or a related discipline.

  2. An emerging publication record in nutrient and water management modelling is mandatory.

  3. Strong statistical analysis; empirical and process-based modeling through any appropriate models and models like AQUACROP, WABAL, EPIC, DDSAT, APSIM, and SPSS, etc.

  4. Capable of using at least two of the following programming skills: R, Python, Matlab.

  5. Knowledge of nutrient and water management repositories.

Candidates should be particularly motivated by and interested in the impacts of climate change on arid food systems and on how nutrient and water management can be used to fix gaps. Proven experience and skills in the use of process-based models in assessing crop response to environmental conditions is at the core. Candidates must have experience in the use of software such as Python, R Programming, SPSS, among others. The ideal candidate should have a strong understanding and ability to use systematic reviewing techniques. Publication record and the ability to take initiative, work independently, develop, and design their own proposals as well as teamwork are an added advantage.

Applications:Use this link to apply (https://www.researchgate.net/job/963248_Post-Doctoral_Fellowship_in_Closing_Yield_Gaps_via_Nutrient_and_Water_Management)

Applications must include the following: 1) a cover letter 2) a detailed Curriculum Vitae, 3) Certified copies of all transcripts at bachelors, masters, and PhD or equivalent, 4) Electronic copy of the PhD thesis 5) Two relevant publications 6) Letter of motivation, 7) Research proposal of three pages maximum and 8) Two reference letters.

Deadline for applications: 30th May 2022.

For any enquiry, please contact PAMOCPP PI: Prof. Dr. Terence Epule Epule (epule.terence@um6p.ma), Prof. Dr. Victor Ongoma (victor.ongona@um6p.ma) and the program lead of IWRI: Prof. Abdelghani Chehbouni (abdelghani.chehbouni@um6p.ma)

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4. Position Announcement: Post-Doctoral Fellowship

Job Title: Using Machine Learning Approaches to Predict Yield and Precipitation Gaps in Morocco.

Area of specialization in IWRI: Machine Learning Applications in Climate Change Impacts on Agriculture

Job description:

We are in search for a one-year term (renewable) post-doctoral fellow to work on the above topic. The focus of this PDF will be to identify ways of closing yield and precipitation gaps through nutrient and water management options. Machine leaning approaches can be particularly useful here in predicting yields and precipitation gaps. Machine learning techniques (Artificial Neural Network-ANN and Support Vector Machines-SVM) go beyond yield and precipitation prediction based on historical data to incorporate computer vision technologies to provide data on weather economic conditions. In addition, machine learning can enhance other facets such as cultivar selection, soil and water management and disease detection. This can evidently provide more data that can be given to farmers and researcher through the app and the data platform, respectively. These models can be parametrized using data outputs from previous stages above.

Key duties:

The key deliverables will include:

1) To conduct systematic reviews to identify the current research gaps in this area of research.

2) Using machine learning approaches to predict past, present, and future yield and precipitation gaps in Morocco at a National Scale.

3) Identify the drivers of Yield and Precipitation Gaps (Biophysical and Non-biophysical)

Criteria of the candidate:

The ideal candidate should:

  1. Must have completed a PhD degree in geography, agronomy, agriculture, water and resource management, and earth or environmental sciences or a related discipline.

  2. An emerging publication record in nutrient and water management modelling is mandatory.

  3. Strong empirical and machine learning skills and applications in climate change and agriculture.

  4. Capable of using at least two of the following software to analyse data such as SPSS, excel, R, python and Matlab.

Candidates should be particularly motivated by and interested in machine learning applications in climate change and impacts on arid food systems at different scales. Candidates must have experience in the use of software such as Python, R Programming, SPSS, excel and others. The ideal candidate should have a strong understanding and ability to use systematic reviewing techniques. Candidates with emerging publication records and the ability to take initiative, work independently, develop, and design their own proposals as well as work in groups is an asset.

Applications: use this link to apply(https://www.researchgate.net/job/963249_Post-Doctoral_Fellowship_in_Using_Machine_Learning_Approaches_to_Predict_Yield_Precipitation_gaps)

Applications must include the following: 1) a cover letter 2) a detailed Curriculum Vita, 3) CERTIFIED copies of all transcripts at bachelors, masters, and PhD or equivalent, 4) Electronic copies of the PhD thesis, 5) Two related publications, 6) Cover letter 7) Letter of motivation, 8) Research proposal of three pages maximum and 9) Two letters of reference.

Deadline for applications: May 30th, 2022.

For any enquiry, please contact PAMOCPP PI: Prof. Dr. Terence Epule Epule (epule.terence@um6p.ma), Prof. Dr. Ikram Chairi (ikram.chairi@um6p.ma) and the program lead of IWRI: Prof. Abdelghani Chehbouni (abdelghani.chehbouni@um6p.ma)

 

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