Skip to main content

PhD position (f/m/x) – Climate extremes in tropical ecosystems - an assessment through data and models Helmholtz-Zentrum für Umweltforschung - UFZ






PhD position (f/m/x) – Climate extremes in tropical ecosystems - an assessment through data and models Helmholtz-Zentrum für Umweltforschung - UFZ


The Helmholtz Centre for Environmental Research (UFZ) with its 1,100 employees has gained an excellent reputation as an international competence centre for environmental sciences. We are part of the largest scientific organisation in Germany, the Helmholtz association. Our mission: Our research seeks to find a balance between social development and the long-term protection of our natural resources.
The newly established Department of Remote Sensing in UFZ in tandem with the Remote Sensing Centre for Earth System Research (RSC4Earth.de) - a joint initiative of UFZ and the Faculty of Physics and Earth Sciences at Leipzig University - conducts innovative research to advance the understanding of the Earth system via the integration of various remote sensing, data science, and process-oriented modelling techniques. It has extensive research experience in quantifying land surface dynamics from multi-source Earth observations across scales.
Within the PhD framework "MoDEV - Towards novel model-data fusion for understanding environmental variability in space and time from high-resolution remote sensing" we are seeking to appoint a highly motivated candidate for the PhD project on "Climate extremes in tropical ecosystems - an assessment through data and models".
PhD position (f/m/x) – Climate extremes in tropical ecosystems - an assessment through data and models
Working time: 65% (25.35 hours per week), limited to 3 years
Your tasks:
This PhD project aims to understand the impact of extreme events (e.g. drought, heat wave) on ecosystem dynamics in the tropics. We are interested in understanding the role of land-surface dynamics on different ecosystems based on satellite observations and model simulations. Key research questions include:
What are the spatiotemporal dynamics of climate-induced extreme events in tropical forests and how do their impacts and characteristics change regionally as a function of environmental conditions?
What is the role of species and structural diversity in buffering the impacts of climate extremes; can we describe gradients of resilience within tropical forest ecosystems?
To achieve this goal, optimal data-fusion strategies for merging satellite remote sensing data and models with different spatial and temporal resolutions shall be developed
The PhD project will be supervised by Prof. Miguel Mahecha (UFZ and Leipzig University) and Prof. Andreas Huth (UFZ).
Your profile:
Master degree (or equivalent) in Earth system (data-) science, computer sciences, remote sensing, hydrology, meteorology, applied mathematics, or any related field.
Fluency in one language of scientific computing (e.g., Julia, Python, Fortran, R)
Ideally a solid background in either machine-learning or dynamical modelling
Genuine interest in understanding how the Earth system works!
Willingness to publish results in peer-reviewed journals and present at scientific meetings
Good communication skills in English, and strong interest to work in an interdisciplinary research team
We offer:
Excellent technical facilities which are without parallel
The freedom you need to bridge the difficult gap between basic research and close to being ready for application
Work in interdisciplinary, multinational teams
Excellent links with national and international research networks
Excellent support and optimal subject-specific and general training with our HIGRADE graduate school
Remuneration in accordance with the TVöD public-sector pay grade 13 (65%)





Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
https://www.facebook.com/Applied.Geography
http://geogisgeo.blogspot.com

Comments

Popular posts from this blog

Platforms in Remote Sensing

In remote sensing, a platform is the physical structure or vehicle that carries a sensor (camera, scanner, radar, etc.) to observe and collect information about the Earth's surface. Platforms are classified mainly by their altitude and mobility : Ground-Based Platforms Definition : Sensors mounted on the Earth's surface or very close to it. Examples : Tripods, towers, ground vehicles, handheld instruments. Applications : Calibration and validation of satellite data Detailed local studies (e.g., soil properties, vegetation health, air quality) Strength : High spatial detail but limited coverage. Airborne Platforms Definition : Sensors carried by aircraft, balloons, or drones (UAVs). Altitude : A few hundred meters to ~20 km. Examples : Airplanes with multispectral scanners UAVs with high-resolution cameras or LiDAR High-altitude balloons (stratospheric platforms) Applications : Local-to-regional mapping ...

Model GIS object attribute entity

These concepts explain different ways of organizing, storing, and representing geographic information in a Geographic Information System (GIS) . They include database design models (ER model), data structure models (Object and Attribute models), and spatio-temporal representations that integrate location, entities, and time . Together, they help GIS manage both spatial data (where things are) and descriptive information (what they are and how they change over time) . 1. Object-Based Model (Object-Oriented Data Model) The Object-Based Model treats geographic features as independent objects that combine spatial geometry and descriptive attributes within a single structure. Core Concept: Each geographic feature (such as a building, road, or river ) is represented as a self-contained object that stores both: Geometry – location and shape (point, line, polygon) Attributes – descriptive properties (name, type, length, capacity) Unlike older georelational models , which stored spatial ...

Types of Remote Sensing

Remote Sensing means collecting information about the Earth's surface without touching it , usually using satellites, aircraft, or drones . There are different types of remote sensing based on the energy source and the wavelength region used. 🛰️ 1. Active Remote Sensing 📘 Concept: In active remote sensing , the sensor sends out its own energy (like a signal or pulse) to the Earth's surface. The sensor then records the reflected or backscattered energy that comes back from the surface. ⚙️ Key Terminology: Transmitter: sends energy (like a radar pulse or laser beam). Receiver: detects the energy that bounces back. Backscatter: energy that is reflected back to the sensor. 📊 Examples of Active Sensors: RADAR (Radio Detection and Ranging): Uses microwave signals to detect surface roughness, soil moisture, or ocean waves. LiDAR (Light Detection and Ranging): Uses laser light (near-infrared) to measure elevation, vegetation...

Atmospheric Window

The atmospheric window in remote sensing refers to specific wavelength ranges within the electromagnetic spectrum that can pass through the Earth's atmosphere relatively unimpeded. These windows are crucial for remote sensing applications because they allow us to observe the Earth's surface and atmosphere without significant interference from the atmosphere's constituents. Key facts and concepts about atmospheric windows: Visible and Near-Infrared (VNIR) window: This window encompasses wavelengths from approximately 0. 4 to 1. 0 micrometers. It is ideal for observing vegetation, water bodies, and land cover types. Shortwave Infrared (SWIR) window: This window covers wavelengths from approximately 1. 0 to 3. 0 micrometers. It is particularly useful for detecting minerals, water content, and vegetation health. Mid-Infrared (MIR) window: This window spans wavelengths from approximately 3. 0 to 8. 0 micrometers. It is valuable for identifying various materials, incl...

geostationary and sun-synchronous

Orbital characteristics of Remote sensing satellite geostationary and sun-synchronous  Orbits in Remote Sensing Orbit = the path a satellite follows around the Earth. The orbit determines what part of Earth the satellite can see , how often it revisits , and what applications it is good for . Remote sensing satellites mainly use two standard orbits : Geostationary Orbit (GEO) Sun-Synchronous Orbit (SSO)  Geostationary Satellites (GEO) Characteristics Altitude : ~35,786 km above the equator. Period : 24 hours → same as Earth's rotation. Orbit type : Circular, directly above the equator . Appears "stationary" over one fixed point on Earth. Concepts & Terminologies Geosynchronous = orbit period matches Earth's rotation (24h). Geostationary = special type of geosynchronous orbit directly above equator → looks fixed. Continuous coverage : Can monitor the same area all the time. Applications Weather...