[robotics-worldwide] [jobs] PhD candidate - Bumblebees in the spotlight: Studying the visual-motor interactions in the flight system of pollinating bumblebees
florianmuijres at gmail.com
Wed Sep 13 07:48:00 PDT 2017
PhD candidate - Bumblebees in the spotlight: Studying the visual-motor interactions in the flight system of pollinating bumblebees
- Location: Wageningen University, The Netherlands
- Scientific field: Natural Sciences/Physics/Engineering
- Apply at: https://urldefense.proofpoint.com/v2/url?u=https-3A__tinyurl.com_y9ysscp8&d=DwIFaQ&c=clK7kQUTWtAVEOVIgvi0NU5BOUHhpN0H8p7CSfnc_gI&r=0w3solp5fswiyWF2RL6rSs8MCeFamFEPafDTOhgTfYI&m=r2FcugcOmAoQwyjYcMbwjhl4P6Va1t9TzIYxVNdd3fk&s=Diqrd11FjQ107f19aaiQloNtXY1iwDwutN40wvT7nII&e=
We are looking for a highly motivated and skilled PhD candidate to study the visual- flight motor system of bumblebees, and its dependency on light conditions.
Bumblebees are the most widely used pollinators in horticulture, and therefore they have become a model-species for studying insect flight and vision. To successfully forage, bumblebees need to detect, approach, and land on flowers. All these steps are primarily controlled by sophisticated interactions between vision and flight motor control (Figure 1). Because the performance of the visual system deteriorates with a reduction in light intensity, flight control is also negatively affected in dim light conditions. This might be an important factor for explaining the reduced pollination rates of bumblebees in relatively dimly-lit greenhouses.
The PhD candidate will study how the visual-flight motor system of bumblebees is affected by light conditions. For this, the PhD candidate will perform a set of experiments on bumblebees landing on artificial flowers, in various light conditions.
Based on these experiments, the candidate will derive the functional dynamics of the visual-flight motor system of bumblebees, and determine how low light conditions affect landing performance, and consequently pollination rates. The results will contribute to the fundamental understanding of the co-evolution of flowers and insects, as well as the co-evolution of the visual system and flight control in the most widely-used pollinator in horticulture.
For this project, a range of experimental and modelling tools are available at Wageningen University, including a dedicated insect flight arena with a high-speed camera system for tracking flying insects. Using this system, the PhD candidate can, for example, perform closed-loop experiments on bumblebees landing on artificial robotic flowers, whereby robotic flower movements are controlled based on the position of the bumblebee. The candidate is expected to perform part of the research abroad in collaboration with our international partners.
For this interdisciplinary project, we are looking for a highly motivated and skilled PhD candidate with a recent university MSc degree (or equivalent) in biology, engineering or (bio)physics. Specific requirements are:
- Strong analytical/modeling skills and innovative attitude.
- A clear affinity with the field of (bio)physics, (bio)mechanics, mathematics and/or animal behavior/ecology.
- Very good programming skills (e.g. Matlab, R or Python).
- The candidate should be a team player with excellent communication skills.
- Proficient in English (both oral and written).
We offer a full-time appointment (1.0 fte, 38 hours/week) for 4 years (18+30 months). Salary ranges from € 2222,- (gross) in the first year to € 2840,- (gross) in the fourth year based on full-time employment.
For more information, please contact Dr ir Florian T Muijres (florian.muijres at wur.nl | +31 317 486 977).
Applications have to be submitted via the Wageningen UR online application system. Candidates are requested to upload the following information to the website:
- Letter of motivation
- CV, including GPA (Grade Point Average) or equivalent in your Bachelor and Master education
- Names and contact information for two references
You can apply until October 16th, 2017.
Job interviews will be held in November 2017.
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