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

Post a Comment

Popular posts from this blog

Evaluation and Characteristics of Himalayas

Time Period Event / Process Geological Evidence Key Terms & Concepts Late Precambrian – Palaeozoic (>541 Ma – ~250 Ma) India part of Gondwana , north bordered by Cimmerian Superterranes, separated from Eurasia by Paleo-Tethys Ocean . Pan-African granitic intrusions (~500 Ma), unconformity between Ordovician conglomerates & Cambrian sediments. Gondwana, Paleo-Tethys Ocean, Pan-African orogeny, unconformity, granitic intrusions, Cimmerian Superterranes. Early Carboniferous – Early Permian (~359 – 272 Ma) Rifting between India & Cimmerian Superterranes → Neotethys Ocean formation. Rift-related sediments, passive margin sequences. Rifting, Neotethys Ocean, passive continental margin. Norian (210 Ma) – Callovian (160–155 Ma) Gondwana split into East & West; India part of East Gondwana with Australia & Antarctica. Rift basins, oceanic crust formation. Continental breakup, East Gondwana, West Gondwana, oceanic crust. Early Cretaceous (130–125 Ma) India broke fr...
Post a Comment
Read more

Seismicity and Earthquakes, Isostasy and Gravity

1. Seismicity and Earthquakes in the Indian Subcontinent Key Concept: Seismicity Definition : The occurrence, frequency, and magnitude of earthquakes in a region. In India, seismicity is high due to active tectonic processes . Plate Tectonics 🌏 Indian Plate : Moves northward at about 5 cm/year. Collision with Eurasian Plate : Causes intense crustal deformation , mountain building (Himalayas), and earthquakes. This is an example of a continental-continental collision zone . Seismic Zones of India Classified into Zone II, III, IV, V (Bureau of Indian Standards, BIS). Zone V = highest hazard (e.g., Himalayas, Northeast India). Zone II = lowest hazard (e.g., parts of peninsular India). Earthquake Hazards ⚠️ Himalayas: prone to large shallow-focus earthquakes due to active thrust faulting. Northeast India: complex subduction and strike-slip faults . Examples: 1897 Shillong Earthquake (Magnitude ~8.1) 1950 Assam–Tib...
Post a Comment
Read more

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...
Post a Comment
Read more

Network data model

GIS, a network data model is used to represent and study things that are connected like a web — for example, roads, rivers, railway tracks, water pipes, or electric lines . It focuses on how things are connected and helps us solve problems like finding the best route, the nearest hospital, or where water will flow. Nodes → Points where things meet or end (e.g., road intersections, railway stations, pumping stations). Edges → Lines connecting the nodes (e.g., roads, pipelines, cables). Topology → The "rules" of connection — which node is linked to which edge. Attributes → Extra details about each part (e.g., road speed limit, pipe size, traffic volume). How It Works 🔍 Make the Network Model Start with a map of lines (roads, pipes, rivers) and mark how they connect. Run Analyses Routing → Find the shortest or fastest path. Closest Facility → Find the nearest hospital, petrol station, etc. Service Area → Find how far y...
Post a Comment
Read more

Pre During and Post Disaster

Disaster management is a structured approach aimed at reducing risks, responding effectively, and ensuring a swift recovery from disasters. It consists of three main phases: Pre-Disaster (Mitigation & Preparedness), During Disaster (Response), and Post-Disaster (Recovery). These phases involve various strategies, policies, and actions to protect lives, property, and the environment. Below is a breakdown of each phase with key concepts, terminologies, and examples. 1. Pre-Disaster Phase (Mitigation and Preparedness) Mitigation: This phase focuses on reducing the severity of a disaster by minimizing risks and vulnerabilities. It involves structural and non-structural measures. Hazard Identification: Recognizing potential natural and human-made hazards (e.g., earthquakes, floods, industrial accidents). Risk Assessment: Evaluating the probability and consequences of disasters using GIS, remote sensing, and historical data. Vulnerability Analysis: Identifying areas and p...
Post a Comment
Read more