Skip to main content

PhD Positions - Remote Sensing for Precision Agriculture and Plant Phenotyping TU München






PhD Positions - Remote Sensing for Precision Agriculture and Plant Phenotyping TU München


The Precision Agriculture Lab at Technical University of Munich (TUM) is seeking applications for Research Assistant positions (TV-L E13, 50%) for pursuing Ph.D. degree with a research focus on remote sensing for precision agriculture and plant phenotyping. The position is limited to 36 months. Extension is negotiable depending on funds. The Precision Agriculture Lab is newly established within the Department of Life Science Engineering, TUM School of Life Sciences. We conduct interdisciplinary research from a diversity perspective of precision agriculture (or precision/smart farming). We focus on studying plant-environment interactions and their control from multiple scales by applying and integrating a range of imaging, remote sensing, statistical modeling, and computational techniques. We are seeking creative candidates who are enthusiastic about interdisciplinary research in precision agriculture – For instance, using cutting-edge sensing and modeling techniques to quantitatively characterize crop stress response and field variability, plant traits, and biodiversity; studying the underlying eco-physiological and genetic basis; and formulating technical strategies for smart farming and sustainable agriculture. Candidates will have the opportunity to work within a stimulating research environment with an interdisciplinary team. The successful candidates will be employed by TUM. You will not only work on your doctoral dissertation but also perform a wide range of research and teaching tasks. You will produce project reports, present research findings in conferences, and publish research findings in peer-reviewed journals.
Requirements:
• Master's degree in remote sensing, agricultural science, ecology, geoinformation science, agricultural engineering, biosystems engineering, or related fields.
• Expertise in remote sensing, handling big data (e.g. spectral and spatial data analyses).
• Skills in programming (e.g., R/Python/Matlab) and image processing.
• Knowledge about precision agriculture, GIS, drones, plant phenotyping, biodiversity.
• Desirable to have experience in computer vision, machine learning and deep learning.
• Proficiency in English (both oral and writing skills).
• Motivation to perform field and lab work.
• Ability to work independently as well as collaboratively in an international and interdisciplinary team.

As an equal opportunity and affirmative action employer, TUM encourages application from women as well as from all others who would bring additional diversity to the university's research and teaching strategies. Preference will be given to disabled candidates with essentially the same qualifications.

Application:
To apply, please submit your application including the following documents: 1) letter of motivation, 2) CV, 3) copies of university degree certificates and transcripts, 4) names and contact information of three references. Please send you application in a single PDF file, with the subject format 'TUM Precision Agriculture PhD Position Application', to pa@wzw.tum.de by 15.09.2020 for full consideration. Interviews of invited candidates will be held at the end of September 2020.

Contact:
Prof. Dr. Kang Yu
Precision Agriculture
Technical University of Munich
Dürnast 3, D-85354 Freising, Germany
Phone: +49 (0)81 6171 5001
Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.



....
Warm Regards

Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
http://geogisgeo.blogspot.com
🌏🌎
🌐🌍

Comments

Popular posts from this blog

Optical Sensors in Remote Sensing

1. What Are Optical Sensors? Optical sensors are remote sensing instruments that detect solar radiation reflected or emitted from the Earth's surface in specific portions of the electromagnetic spectrum (EMS) . They mainly work in: Visible region (0.4–0.7 µm) Near-Infrared – NIR (0.7–1.3 µm) Shortwave Infrared – SWIR (1.3–3.0 µm) Thermal Infrared – TIR (8–14 µm) — emitted energy, not reflected Optical sensors capture spectral signatures of surface features. Each object reflects/absorbs energy differently, creating a unique spectral response pattern . a) Electromagnetic Spectrum (EMS) The continuous range of wavelengths. Optical sensing uses solar reflective bands and sometimes thermal bands . b) Spectral Signature The unique pattern of reflectance or absorbance of an object across wavelengths. Example: Vegetation reflects strongly in NIR Water absorbs strongly in NIR and SWIR (appears dark) c) Radiance and Reflectance Radi...

Radar Sensors in Remote Sensing

Radar sensors are active remote sensing instruments that use microwave radiation to detect and measure Earth's surface features. They transmit their own energy (radio waves) toward the Earth and record the backscattered signal that returns to the sensor. Since they do not depend on sunlight, radar systems can collect data: day or night through clouds, fog, smoke, and rain in all weather conditions This makes radar extremely useful for Earth observation. 1. Active Sensor A radar sensor produces and transmits its own microwaves. This is different from optical and thermal sensors, which depend on sunlight or emitted heat. 2. Microwave Region Radar operates in the microwave region of the electromagnetic spectrum , typically from 1 mm to 1 m wavelength. Common radar frequency bands: P-band (70 cm) L-band (23 cm) S-band (9 cm) C-band (5.6 cm) X-band (3 cm) Each band penetrates and interacts with surfaces differently: Lo...

Thermal Sensors in Remote Sensing

Thermal sensors are remote sensing instruments that detect naturally emitted thermal infrared (TIR) radiation from the Earth's surface. Unlike optical sensors (which detect reflected sunlight), thermal sensors measure heat energy emitted by objects because of their temperature. They work mainly in the Thermal Infrared region (8–14 µm) of the electromagnetic spectrum. 1. Thermal Infrared Radiation All objects above 0 Kelvin (absolute zero) emit electromagnetic radiation. This is explained by Planck's Radiation Law . For Earth's surface temperature range (about 250–330 K), the peak emitted radiation occurs in the 8–14 µm thermal window . Thus, thermal sensors detect emitted energy , not reflected sunlight. 2. Emissivity Emissivity is the efficiency with which a material emits thermal radiation. Values range from 0 to 1 : Water, vegetation → high emissivity (0.95–0.99) Bare soil → medium (0.85–0.95) Metals → low (0.1–0.3) E...

Geometric Correction

When satellite or aerial images are captured, they often contain distortions (errors in shape, scale, or position) caused by many factors — like Earth's curvature, satellite motion, terrain height (relief), or the Earth's rotation . These distortions make the image not properly aligned with real-world coordinates (latitude and longitude). 👉 Geometric correction is the process of removing these distortions so that every pixel in the image correctly represents its location on the Earth's surface. After geometric correction, the image becomes geographically referenced and can be used with maps and GIS data. Types  1. Systematic Correction Systematic errors are predictable and can be modeled mathematically. They occur due to the geometry and movement of the satellite sensor or the Earth. Common systematic distortions: Scan skew – due to the motion of the sensor as it scans the Earth. Mirror velocity variation – scanning mirror moves at a va...

LiDAR in Remote Sensing

LiDAR (Light Detection and Ranging) is an active remote sensing technology that uses laser pulses to measure distances to the Earth's surface and create high-resolution 3D maps . LiDAR sensors emit short pulses of laser light (usually in the near-infrared range) and measure the time it takes for the pulse to return after hitting an object. Because LiDAR measures distance very precisely, it is excellent for mapping: terrain vegetation height buildings forests coastlines flood plains ✅ 1. Active Sensor LiDAR sends its own laser energy, unlike passive sensors that rely on sunlight. ✅ 2. Laser Pulse LiDAR emits thousands of pulses per second (even millions). Wavelengths commonly used: Near-Infrared (NIR) → land and vegetation mapping Green (532 nm) → water/ bathymetry (penetrates shallow water) ✅ 3. Time of Flight (TOF) The sensor measures the time taken for the laser to travel: from the sensor → to the sur...