Skip to main content

PhD, PostDoc, Group Leader and Guest Professor Positions in the area of Machine Learning and Data Analytics in Earth Observation (AI4EO).


we have several open PhD, PostDoc, Group Leader and Guest Professor Positions in the area of Machine Learning and Data Analytics in Earth Observation (AI4EO).
PhD, PostDoc, and Group Leader (Wissenschaftliche/r Mitarbeiter/in)
 

Zhu lab is a joint venue of the Professorship for Signal Processing in Earth Observation at the Technical University of Munich [www.sipeo.bgu.tum.de] and the Department EO Data Science of the Remote Sensing Technology Institute of the German Aerospace Center (DLR) [https://www.dlr.de/eoc/en/desktopdefault.aspx/tabid-12785/22743_read-52854/]. We develop innovative signal processing and machine learning algorithms to extract geo-information from big geospatial data, ranging from remote sensing satellite data and even social media data. As downstream applications, we provide large scale and highly accurate geo-information to address societal grand challenges, such as monitoring the global urbanization, climate research and supporting the sustainable development goals of the United Nations. Our lab offers currently several open positions for outstanding PhD Candidates, postdocs, and senior scientists at either the Technical University Munich (TUM) or the German Aerospace Center (DLR). We also have open positions for outstanding research engineers.

 

Topics of particular interest to the group include:

-        Earth Observation and Computer Vision

-        Machine Learning/Deep Learning

-        Unsupervised/weakly Supervised Learning

-        Uncertainty Analysis, Interpretation and Reasoning of Deep Neural Networks 

-        AutoML

-        Anomaly and Change Detection Methods

-        Geo-information Extraction from Social Media Data

-        Natural Language Processing

-        Large-Scale Data Mining and Knowledge Discovery in Earth Observation

-        Big Data Management

-        High-performance Computing

-        Statistical Learning, Modelling, Spatial and Temporal Analysis of Geographical Observations

-        Geo-referencing, Digitalization, Building and Maintaining Large Relational Data Bases and Geo-databases, Publishing Geo-services (i.e. Web Map Services)

 

Demonstrated hands-on experience in one or more of these areas is a requirement. Postdoc applicants should have an excellent publication record and a PhD in machine learning, computer science, statistics, remote sensing, mathematics or a related discipline. Research engineer applicants should have excellent coding skills, as well as practical skills in data science and/or deep learning, and experience with scripting and running large-scale experiments.

 

Application materials comprise:

-        CV

-        Full set of transcripts

-        Statement of purpose

-        Briefly state what drives you and what are your goals in applying to the SiPEO lab

-        Names for at least 2 reference letter writers

                             For each reference, please include name, title, and email address.

                             References should expect to be contacted for a reference letter.

 

Please submit these documents to ai@DLR.de.  Please kindly consider that due to the high requests, we will not be able to consider incomplete applications.

 

AI4EO Guest Professors
 

In the framework of the BMBF funded German International AI Future Lab AI4EO, we have also a couple of slots free for guest professors with a pay scale from W1 to W3. Should you be working on any of the three topics 1) reasoning; 2) uncertainty and 3) Ethics in AI4EO and be interested in visiting us in Munich for 18 to 36 month, please kindly in direct contact with Prof. Dr. Xiaoxiang Zhu (xiaoxiang.zhu@dlr.de)

 

About Us:

 

The Technical University of Munich (TUM):

The Technical University of Munich (TUM) is one of Europe's top universities. It is committed to excellence in research and teaching, interdisciplinary education and the active promotion of promising young scientists. The university also forges strong links with companies and scientific institutions across the world. TUM was one of the first universities in Germany to be named a University of Excellence. Moreover, TUM regularly ranks among the best European universities in international rankings.

 

German Aerospace Center (DLR):

As a member of the Helmholtz Association of German Research Centers, the German Aerospace (DLR) employs more than 8000 people at 20 locations. The department "EO Data Science" at the Remote Sensing Technology Institute (IMF-DAS), located at the DLR in Oberpfaffenhofen is developing novel signal processing and AI algorithms to improve information retrieval from remote sensing data, in particular those from current and the next generation of Earth observation missions and deliver crucial geo-information to address social grant challenges, such as urbanization and climate change.

 

Resources and opportunities for collaboration:

·       Both at TUM and DLR, we are equipped with state-of-the-art computational resources such as DGX servers. In addition, we are closely collaborating with the Leibniz Supercomputing Centre (LRZ), which provides us with access to one of the most powerful supercomputing environments in Europe.

 

·       Helmholtz AI: The Helmholtz AI [link] platform aims to enhance the research within the Helmholtz Association with applied AI methods. For that each research area of Helmholtz operates HAICU units to work on short, medium and long term AI projects. IMF-DAS operates the local Helmholtz AI unit "MASTr: HAICU Munich @ Aeronautics, Space and Transport". It consists of a Young Investigator Group (YIG) in Earth observation and an AI Consulting Team, providing the expertise from Earth Observation, robotics, computer vision and an HPC/HPDA support unit. Currently we are looking for an enthusiastic Head of the YIG in the field of Large-Scale Data Mining in Earth Observation, and two PhD students.

 

·       Future AI Lab on Artificial Intelligence in Earth Observation: For the BMBF-funded Future Lab on Artificial Intelligence in Earth Observation (AI4EO), we are looking for one science manager and two PostDocs to form the backbone team of the lab starting from May 1, 2020. The Future Lab will bring together 12 highly renowned senior scientists and dozens of junior scientists from across the globe to carry out cutting-edge AI4EO research that will help to bring AI4EO to the next level. The research topics include but are not limited to reasoning, uncertainty and ethics in AI4EO.

 

 

Best regards,

Xiaoxiang Zhu

 

——————————————————

Prof. Dr.-Ing. habil. Xiaoxiang Zhu

Direcor of the German International Future AI Lab „AI4EO"

Technical University of Munich (TUM) & German Aerospace Center (DLR)

Department of Aerospace and Geodesy| Willy-Messerschmitt-Str. 1 | 82024 Taufkirchen/Ottobrunn | Germany
Website: www.ai4eo.de (up soon)

Head of Department "EO Data Science"

German Aerospace Center (DLR)

Earth Observation Center | Remote Sensing Technology Institute | Department of EO Data Science | Oberpfaffenhofen | 82234 Wessling | Germany

Telephone +49 81-5328-3531 | Telefax +49 81-5328-1420 | xiaoxiang.zhu@dlr.de

 

Professor for Signal Processing in Earth Observation

Technical University of Munich (TUM)
Signal Processing in Earth Observation| Arcisstrasse 21 | 80333 Munich | Germany

Telephone +49 89-289-22659 | Telefax +49 89-289-23202 | xiaoxiang.zhu@tum.de

 

Please visit my DLR-TUM joint research group here http://www.sipeo.bgu.tum.de/


🌍
🌏
🌎
🌐
😀
👍🏾
#Globe
#Earth
#Map
#Decision Making
#Cartography
#Cartographer
#Geography
#Geographer
#GIS
#Remote_Sensing
#RemoteSensing, #GeospatialEducation, #GeoEducation, #government, #LocalGovernment, #BigData, #geospatial, #GeoOps #ChangeDetection, #LocationIntelligence, #LocationTechnology, #SmartCities, #SmartCity, #Geomatics, #Geoinformatics, #Geology, #surveying
#StaySafe, #StayHome, #StayHealthy
#Scholarship, #Scholarships, #Onlinecourse, #Onlineducation

....


Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
https://g.page/vineeshvc

Comments

Post a Comment

Popular posts from this blog

Geography of Landslides. Mitigation and Resilience.

A landslide is a geological event in which a mass of rock, earth, or debris moves down a slope under the force of gravity. Landslides can range in size from small to large and can be triggered by natural events such as heavy rainfall, earthquakes, or volcanic activity, or by human activities such as construction or mining. The geography of landslides is affected by a variety of factors that can increase the likelihood of landslides occurring in a particular area. These factors include slope angle and steepness, the type of soil and rock present, the climate and weather patterns of the region, the presence or absence of vegetation, and human activities such as construction, mining, and deforestation. Areas with steep slopes are more prone to landslides because gravity has a stronger effect on loose soil and rock, making it more likely to move downhill. Similarly, areas with loose, sandy soil or weak, fractured rock are more prone to landslides because they are less stable and more easil
Post a Comment
Read more

Disaster Management. Geography of Disaster Management.

Disaster management refers to the process of preparing for, responding to, and recovering from disasters or emergencies that may affect communities, regions, or entire countries. It involves the coordination of various activities and efforts by government agencies, non-governmental organizations, and other stakeholders to minimize the impact of disasters and promote the well-being of affected populations. The process of disaster management can be broken down into four phases: Mitigation: This involves taking steps to reduce the risk of disasters, such as identifying and addressing potential hazards, developing emergency plans, and improving infrastructure and systems. Preparedness: This involves preparing for the possibility of a disaster, such as training emergency responders, conducting drills and exercises, and stockpiling necessary supplies. Response: This involves taking immediate action during and immediately after a disaster, such as rescuing people, providing emergency medical
Post a Comment
Read more

Landslide

Landslides are a type of "mass wasting," where soil and rock move down-slope due to gravity. Landslides can be caused by a combination of factors, such as rainfall, snowmelt, changes in water level, and human activities. There are five modes of slope movement, including falls, topples, slides, spreads, and flows, which vary depending on the type of geologic material. Debris flows and rock falls are common types of landslides. Landslides can also occur underwater, known as submarine landslides, and sometimes cause tsunamis. Landslides occur when down-slope forces exceed the strength of the earth materials that compose the slope. Slopes already on the verge of movement are more susceptible to landslides, which can be induced by earthquakes, volcanic activity, and stream erosion.  There are four main types of movement: falls, topples, slides (rotational and translational), and flows. Landslides can involve just one of these movements or a combination of several. Geologists also
Post a Comment
Read more

Disaster Management Act, 2005. National Disaster Management Framework (NDMF) National Disaster Management Authority (NDMA). National Institute of Disaster Management (NIDM). National Disaster Response Force (NDRF)

Disaster Management Act, 2005. National Disaster Management Framework (NDMF) National Disaster Management Authority (NDMA). National Institute of Disaster Management (NIDM). National Disaster Response Force (NDRF) The National Disaster Management Framework (NDMF) in India is a comprehensive policy document that provides a framework for managing disasters in the country. The framework was first introduced in 2005 and was updated in 2019. The NDMF is based on the principle of an integrated approach to disaster management. It aims to bring together all stakeholders, including the government, non-governmental organizations (NGOs), civil society, and the private sector, to work towards a common goal of disaster management. The framework is designed to address all phases of disaster management, including prevention, preparedness, response, and recovery. It provides guidelines for various aspects of disaster management, including risk assessment, disaster planning, early warning systems, sear
Post a Comment
Read more

Landslides. USGS

Landslides. TYPES OF LANDSLIDES The term "landslide" describes a wide variety of processes that result in the downward and outward movement of slope-forming materials including rock, soil, artificial fill, or a combination of these. The materials may move by falling, toppling, sliding, spreading, or flowing. The animated GIF shows a graphic illustration of different types of landslides, with the commonly accepted terminology describing their features. The various types of landslides can be differentiated by the kinds of material involved and the mode of movement.
Post a Comment
Read more