Skip to main content

ASSISTANT PROFESSOR Vacancy


ASSISTANT PROFESSOR IN 

The Department of Earth Systems Analysis of the Faculty of Geo-information Science and Earth Observation at the University of Twente is looking for an Earth scientist with experience in the assessment of risk of natural hazards to infrastructure and population. The Department of Earth Systems Analysis combines Earth science knowledge with spatial modelling and advanced remote sensing to understand Earth processes in space and time. Our education and research contribute to the sustainable use of energy and Earth resources and help reduce disaster risk and the impact of natural hazards on society.

We are seeking an enthusiastic colleague to complement our existing strengths in natural hazards (Earth structure and dynamics, Hydro-meteorological hazard assessment, Time-variant multi-hazard risks, Climate and disaster resilience, Post disaster damage & recovery assessment). Your tasks will focuses on how to quantity risk of interacting natural hazards for improved disaster risk reduction planning, in a context of changing multi-hazards, exposure and vulnerability, mostly in data scarce environment. You will contribute to the development of methods and tools (Spatial Decision Support System) to quantify multi-hazard risk for gradual changes (e.g. due to climate change), abrupt changes (e.g. after major disasters) and planned changes (risk reduction alternatives). An important component of the work will be to actively participate in project acquisition and execution of externally funded projects related to multi-hazard risk assessment in developing countries.

You also have to:

  • Contribute to the educational programme(s) offered by the department
  • Develop own research in the field of multi-hazard risk modelling, and supervise MSc and PhD students
  • Contribute to the development of the SDSS in terms of architecture, functional specifications, testing, documentation, training and implementing in international projects

YOUR PROFILE

You have:

  • A completed PhD on research related to risk assessment, or about to complete your PhD in the next months.
  • Experience and interest in international projects dealing with the assessment of risk to natural hazards
  • Programming skills and experience with modifying and linking other software tools for hazard and risk assessment.
  • An aptitude for teaching, including lecturing and tutoring at an academic level
  • An affinity with a multi-cultural, post-graduate education environment
  • A willingness to undertake international travel to less developed countries
  • An excellent command of English. Knowledge of, or willingness to learn Dutch, is an advantage.
  • Programming skills the development of software products or components, and experience with the software components mentioned above.


INFORMATION AND APPLICATION

Additional information regarding the position can be obtained from Dr. Cees van Westen (e-mail: c.j.vanwesten@utwente.nl ). You are also invited to visit our homepage.

Please submit your application before 25 January 2020 (choose "apply now" below). Your application has to include (i) a motivation letter clearly stating how you meet the selection criteria and also outlining your research and teaching interests, (ii) a detailed CV with references and (iii) a two-page statement on your vision on research, education and capacity development in relation to ITC, and the position. Applications that do not include all three will not be considered.

A public guest lecture to the ITC-staff can be part of the selection. Because of our diversity values, we do particularly support women and candidates from our target countries and alumni to apply.

OUR OFFER

We offer an inspiring and challenging international environment. You will be initially employed for two years. Extension of the employment after this period is a possibility.

  • Gross monthly salary between € 3545,- and € 4852,- depending on experience and qualifications (job profile Assistant Professor level 2).
  • A holiday allowance of 8% of the gross annual salary and a year-end bonus of 8.3%
  • Excellent support for research and facilities for professional and personal development
  • A solid pension scheme
  • Possibilities to save up holidays for sabbatical leave
  • Minimum of 41 holiday days in case of full-time employment

THE ORGANIZATION

The University of Twente. We stand for life sciences and technology. High tech and human touch. Education and research that matter. New technology which leads change, innovation and progress in society. The University of Twente is the only campus university of the Netherlands; divided over five faculties we provide more than fifty educational programmes. We have a strong focus on personal development and talented researchers are given scope for carrying out groundbreaking research. We are an equal opportunity employer and value diversity at our company.

We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status or disability status. Because of our diversity values we do particularly support women to apply.

The Faculty of Geo-Information Science and Earth Observation (ITC) of the University of Twente provides international postgraduate education, research and project services in the field of geo-information science and earth observation using remote sensing and GIS. The aim of ITC's activities is the international exchange of knowledge, focusing on capacity building and institutional development in developing countries and emerging economies.


---------- Forwarded message ---------
From: 🌐Vineesh V🌏Assistant Professor Geography. Directorate of Collegiate Education. GOVT of Kerala. <vineeshvc@gmail.com>
Date: Tue, 17 Dec, 2019, 9:11 AM
Subject: Fully funded Ph.D. opportunities in remote sensing of vegetation - McMaster University, Canada  
To: <vineeshvc.govt@blogger.com>


Fully funded Ph.D. opportunities in remote sensing of vegetation - McMaster University, Canada  

The Remote Sensing Lab at McMaster University (Hamilton, Ontario, Canada) is seeking two motivated and enthusiastic candidates for the Ph.D. program starting in Fall 2020 or earlier.   

The topics include but not limited to:  

(1) Global change (climate and atmospheric composition) impact assessment on terrestrial ecosystem productivity using long-term satellite data records  

(2) Photosynthesis phenology from satellite based solar-induced chlorophyll fluorescence (SIF) records  

(3) Plant structural and photosynthetic traits at Turkey Point Flux Station and/or Borden Forest Research Station  

Students must have MSc in remote sensing, Earth sciences, meteorology, atmospheric science, physics, or related fields, and good programming skills and remote sensing experience.  

Review of the applications will begin immediately. Qualified candidates should submit a CV and copy of their grade transcripts to Prof. Alemu Gonsamo ([gonsamoa@mcmaster.ca](mailto:gonsamoa@mcmaster.ca)).  


Please do not hesitate to contact me through e-mail if you have any questions regarding this position.  Feel free to forward to anyone who may be interested.

Alemu Gonsamo

Comments

Popular posts from this blog

Accuracy Assessment

Accuracy assessment is the process of checking how correct your classified satellite image is . 👉 After supervised classification, the satellite image is divided into classes like: Water Forest Agriculture Built-up land Barren land But classification is done using computer algorithms, so some areas may be wrongly classified . 👉 Accuracy assessment helps to answer this question: ✔ "How much of my classified map is correct compared to real ground conditions?"  Goal The main goal is to: Measure reliability of classified maps Identify classification errors Improve classification results Provide scientific validity to research 👉 Without accuracy assessment, a classified map is not considered scientifically reliable . Reference Data (Ground Truth Data) Reference data is real-world information used to check classification accuracy. It can be collected from: ✔ Field survey using GPS ✔ High-resolution satellite images (Google Earth etc.) ✔ Existing maps or survey reports 🧭 Exampl...

History of GIS

1. 1832 - Early Spatial Analysis in Epidemiology:    - Charles Picquet creates a map in Paris detailing cholera deaths per 1,000 inhabitants.    - Utilizes halftone color gradients for visual representation. 2. 1854 - John Snow's Cholera Outbreak Analysis:    - Epidemiologist John Snow identifies cholera outbreak source in London using spatial analysis.    - Maps casualties' residences and nearby water sources to pinpoint the outbreak's origin. 3. Early 20th Century - Photozincography and Layered Mapping:    - Photozincography development allows maps to be split into layers for vegetation, water, etc.    - Introduction of layers, later a key feature in GIS, for separate printing plates. 4. Mid-20th Century - Computer Facilitation of Cartography:    - Waldo Tobler's 1959 publication details using computers for cartography.    - Computer hardware development, driven by nuclear weapon research, leads to broader mapping applications by early 1960s. 5. 1960 - Canada Geograph...

Development and scope of Environmental Geography and Recent concepts in environmental Geography

Environmental Geography studies the relationship between humans and nature in a spatial (place-based) way. It combines Physical Geography (natural processes) and Human Geography (human activities). A. Early Stage 🔹 Environmental Determinism Concept: Nature controls human life. Meaning: Climate, landforms, and soil decide how people live. Example: People in deserts (like Sahara Desert) live differently from people in fertile river valleys. 🔹 Possibilism Concept: Humans can modify nature. Meaning: Environment gives options, but humans make choices. Example: In dry areas like Rajasthan, people use irrigation to grow crops. 👉 In this stage, geography was mostly descriptive (explaining what exists). B. Evolution Stage (Mid-20th Century) Environmental problems increased due to: Industrialization Urbanization Deforestation Pollution Geographers started studying: Environmental degradation Resource management Human impact on ecosystems The field became analytical and problem-solving...

Change Detection

Change detection is the process of finding differences on the Earth's surface over time by comparing satellite images of the same area taken on different dates . After supervised classification , two classified maps (e.g., Year-1 and Year-2) are compared to identify land use / land cover changes .  Goal To detect where , what , and how much change has occurred To monitor urban growth, deforestation, floods, agriculture, etc.  Basic Concept Forest → Forest = No change Forest → Urban = Change detected Key Terminologies Multi-temporal images : Images of the same area at different times Post-classification comparison : Comparing two classified maps Change matrix : Table showing class-to-class change Change / No-change : Whether land cover remains same or different Main Methods Post-classification comparison – Most common and easy Image differencing – Subtract pixel values Image ratioing – Divide pixel values Deep learning methods – Advanced AI-based detection Examples Agricult...

Supervised Classification

Image Classification in Remote Sensing Image classification in remote sensing involves categorizing pixels in an image into thematic classes to produce a map. This process is essential for land use and land cover mapping, environmental studies, and resource management. The two primary methods for classification are Supervised and Unsupervised Classification . Here's a breakdown of these methods and the key stages of image classification. 1. Types of Classification Supervised Classification In supervised classification, the analyst manually defines classes of interest (known as information classes ), such as "water," "urban," or "vegetation," and identifies training areas —sections of the image that are representative of these classes. Using these training areas, the algorithm learns the spectral characteristics of each class and applies them to classify the entire image. When to Use Supervised Classification:   - You have prior knowledge about the c...