The Grand Challenge Exploration project “Develop smartphone-based diagnostics platform linking AI image-based disease recognition with microfluidic isothermal amplification diagnostic tools” aims to evaluate if artificial intelligence (AI) can be trained to recognize disease symptoms human eyes cannot appreciate by providing it with pictures of plants together with results of virus status based on sensitive molecular diagnostic tests. .

The consultant will train the AI by taking pictures and performing LAMP assays for three sweetpotato viruses for a minimum of 1,000 leaf samples with virus symptoms and a similar amount of leaves from symptomless sweetpotato plants. Subsequently, improved performance of the app will be evaluated by repeating the procedure with another 500 samples and comparing the predictions made by the AI based on pictures only with that of a crop expert and the results of the molecular tests.

Key responsibilities:

• Partake in (virtual) meetings to understand the concept of the project, expectations and workplan.
• Participate in (remote) LAMP training exercise to get comfortable with the technique.
• Collect pictures and corresponding samples of 2500 individual plants documenting the relationship between them in a predetermined template in a shared folder in the cloud.
• Perform LAMP reactions for 2500 samples for SPFMV and SPCSV and in case of negative samples repeat them with COX primers to confirm adequate quality of RNA.
• Document the relationship between pictures of plants and diagnostic assay results in the predetermined template.
• Organize pictures in folders according to diagnostic result (uninfected, SPFMV, SPCSV or both viruses) for processing by AI.
• ​Draft a scientific manuscript for journal publication based on the study findings.

Requirements

• At least a MSc. in molecular plant pathology (virology) or related field.
• At least 3 years of relevant work experience required in similar position
• Hands-on experience in conducting molecular diagnostic tests using real time PCR
• Strong experience and knowledge of field sample collection, processing and analysis
• First author of at least one peer reviewed journal article in the last two years
• Good photographic skills using a smartphone
• Demonstrated ability to work effectively under tight and strict deadlines and produce quality outputs.

Submit your CV and Application on Company Website : Click Here

Closing Date : 12 July, 2020