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Otto von Guericke University of Magdeburg

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Sustainability Impact Rated
Magdeburg, Germany
601–800th in World University Rankings 2026
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About Otto von Guericke University of Magdeburg

Basic information and contact details for Otto von Guericke University of Magdeburg

Set up in 1993, the University of Magdeburg (OVGU) was founded in 1993 in Germany, and is focused on engineering, natural sciences and medicine. It also offers degrees in economics, management, social sciences and humanities.

 It is located in Magdeburg, the capital city of the federal state of Saxony-Anhalt.

Its research centres on neuroscience, much of which is carried out at the Science Campus Centre for Behavioural Brain Sciences. In terms of engineering research, the university focuses on roof structures and dynamic systems at its Centre for Dynamic Systems. The medical faculty specialises in immunology and the molecular medicine of inflammation. 

Located on the Elbe River, Magdeburg is a scenic medieval city of under 250,000 inhabitants. Its gardens and parks make it one of Germany’s greenest urban areas. The city also hosts high standard professional sport events. The SC Magdeburg is a renown handball team and FC Magdeburg is a well respected football team in Germany. As a student, you can also get discounted tickets to see these teams’ performances. 

Its distinguished alumni include Rumiana Jeleva, former minister of foreign affairs of Bulgaria; the former Prime Minister of Kenya, Raila Odinga; Nguyen Thien Nhan, Vietnam’s deputy prime minister and minister of education and training.

The campus is compact, yet it offers opportunities to get involved in the university’s orchestra, choir and radio. 

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Key Student Statistics

A breakdown of student statistics at Otto von Guericke University of Magdeburg

gender ratio
Student gender ratio
42 F : 58 M (1)
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International student percentage
30% (1)
student per staff
Students per staff
10.7 (1)
student
Student total
12812 (1)

Based on data collected for the (1) World University Rankings 2026

Jobs you might be interested in

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GTI - Postdoctoral Researchers in Artificial Intelligence (AI) – Focus on Large Language Models

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


Call for Postdoctoral Researchers in Artificial Intelligence (AI) – Focus on Large Language Models (LLMs) for Predictive Maintenance: Introduction UM6P Mohammed VI Polytechnic University is an institution dedicated to research and innovation in Africa and aims to position itself among world-renowned universities in its fields The University is engaged in economic and human development and puts research and innovation at the forefront of African development. A mechanism that enables it to consolidate Morocco's frontline position in these fields, in a unique partnership-based approach and boosting skills training relevant for the future of Africa. Located in the municipality of Benguerir, in the very heart of the Green City, Mohammed VI Polytechnic University aspires to leave its mark nationally, continentally, and globally. Context We are seeking a highly motivated and skilled postdoctoral researcher with a strong background in Artificial Intelligence (AI), particularly in the development and application of Large Language Models (LLMs), to join our team working on predictive maintenance solutions. The ideal candidate will have recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply their expertise to advance predictive maintenance systems using AI tools. Key Responsibilities: Conduct innovative research on the application of Large Language Models (LLMs) to predictive maintenance challenges. Develop and fine-tune LLMs to analyze and interpret unstructured data (e.g., maintenance logs, sensor data, technical reports) for predictive insights Collaborate with domain experts to integrate LLM-based solutions into predictive maintenance workflows. Explore the use of LLMs for anomaly detection, failure prediction, and optimization of maintenance schedules. Publish high-impact research in top-tier conferences and journals at the intersection of AI, NLP, and industrial applications. Contribute to the development of scalable and interpretable AI tools for real-world deployment. Qualifications: A PhD in Computer Science, Machine Learning, NLP, or a related field, with a thesis focused on AI, particularly LLMs. Strong publication record in top AI/ML/NLP conferences (e.g., NeurIPS, ICML, ACL, EMNLP, etc.). Proficiency in programming languages such as Python, and experience with deep learning frameworks like TensorFlow, PyTorch, or JAX. In-depth understanding of transformer architectures, attention mechanisms, and fine tuning techniques for LLMs. Experience with time-series data, anomaly detection, or predictive maintenance is a strong plus. Familiarity with industrial datasets and domain-specific challenges is desirable. Excellent problem-solving skills and the ability to work both independently and collaboratively in a team environment. How to Apply: Interested candidates should submit the following documents: A cover letter detailing your research interests and how they align with the application of LLMs to predictive maintenance. A current CV, including a list of publications. Contact information for at least three references. A brief research statement (max 2 pages) outlining your past research and future research directions, particularly as they relate to LLMs

Salary

Competitive

Posted

18 May 2026

COLCOM - Postdoctoral Fellow in Machine Learning

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


Years of Experience: 0 to 4 years Education Level: Doctoral degree  Type of Contract: 1 year contract (renewable) Number of Positions: 2 Expected Start Date: February 1st, 2026 About the University: Located at the heart of the future Green City of Benguerir, Mohammed VI Polytechnic University (UM6P), a higher education institution with an international standard, is established to serve Morocco and the African continent. Its vision is honed around research and innovation at the service of education and development. This unique nascent university, with its state-of-the-art campus and infrastructure, has woven a sound academic and research network, and its recruitment process is seeking high quality academics and professionals in order to boost its quality-oriented research environment in the metropolitan area of Marrakech. About the School The College of Computing (UM6P-CC) is located in the future Green City of Benguerir. It provides world-class university education in computer science promoting discovery and innovation. The College currently offers an engineering degree in computer engineering, and a doctoral program in computer science. About the Group The Data Intelligence Group at UM6P-CC is a growing and supportive team with internationally recognized expertise in data management and machine learning. The group has a strong network of national and international collaborators in both academia and industry. Job Title Postdoctoral Fellow – College of Computing Job Description The Data Intelligence Group at UM6P-CC is seeking two postdoctoral fellows in machine learning who will support the group’s projects in the rapidly growing field of multimodal representation learning and retrieval. The specific responsibilities of the postdoctoral fellow will include: conduct scientific research in the field of machine learning. develop novel machine learning algorithms primarily for representation learning, dimensionality reduction, clustering and search. conduct theoretical and experimental performance analyses of the proposed algorithms. publish research results in high-quality venues (conferences and journals) and present them in national and international scientific events and conferences. contribute to the supervision of undergraduate and graduate students. assist in writing research proposals. contribute to training and teaching activities, including the development of new courses. assist in the organization of workshops, seminars and other national and international events related to machine learning. work effectively with the DMG team and help nurture internal and external collaborations with academic and industrial partners. Qualifications Ph.D. in Computer Science, Applied Mathematics, or a related field. Strong publication record in machine learning, with preference for expertise in representation learning, deep embeddings, contrastive learning, or foundation models. Solid background in linear algebra, probability, and statistics. Strong programming skills with deep learning frameworks (e.g., PyTorch) and standard data analysis tools. Familiarity with data structures, algorithms, and—ideally—search or indexing techniques. Excellent communication skills and strong analytical, teamwork, and organizational abilities. Application: Applications should be submitted online and emailed to karima.echihabi@um6p.ma with the subject "[Postdoctoral Fellow Position]". Ph.D students in their final year of study are also encouraged as long as they expect to obtain their degree by September 2026.  Emailed application materials should contain an up-to-date CV and a zipped archive which includes a cover letter and full transcripts. The CV should clearly indicate the following information: type of high-school degree obtained (e.g., Sciences Mathematiques A), overall high-school average, Mathematics grade in the national exam, and overall average/ranking in university studies. Job Location Benguerir, Morocco

Salary

Competitive

Posted

18 May 2026

GSMI - Postdoctoral Researcher – Potash Brine and Phosphogypsum Valorization

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


Position Title: Postdoctoral Researcher – Potash brine and phosphogypsum valorization. Duration: 12 months. Position Summary: We are seeking a highly motivated and technically skilled postdoctoral researcher to join a multidisciplinary research project dedicated to the sustainable valorization of potash brine and phosphogypsum, with a specific focus on bioleaching technologies. The successful candidate will contribute to advancing the use of environmentally friendly bioleaching techniques for the extraction of valuable resources from these industrial by-products. The project embedded in a circular economy approach aimed at reducing environmental impacts while creating value from industrial co-products, namely phosphogypsum and residual brines generated by sedimentary potash processing activities. The postdoctoral researcher will investigate the valorization of each material separately through physicochemical and biological approaches, with the objective of identifying optimal pathways for resource recovery. The project will also focus on the combined treatment of phosphogypsum and brines, studying the synergistic and symbiotic effects arising from their interaction within integrated bioprocesses. This work will contribute to the development of innovative and sustainable strategies for the recovery of sulfur, magnesium, potassium and other valuable elements from industrial residues. Area of Research: Valorization of industrial by-products derived from sedimentary potash processing and phosphoric acid production. The research will involve physicochemical and biological treatment approaches for potash brines and phosphogypsum, as well as the development of integrated processes exploiting potential synergistic effects between both materials within a circular economy framework. Main responsibilities: Conduct a comprehensive literature review on potash brine management, phosphogypsum valorization, and related physicochemical and biological processing routes. Perform chemical, mineralogical, and physicochemical characterization of potash brines and phosphogypsum. Design and carry out laboratory-scale experiments to investigate separate valorization pathways for brines and phosphogypsum; Develop and evaluate integrated treatment strategies combining both materials, with particular attention to synergistic and symbiotic effects; Study process parameters affecting the recovery of sulfur, magnesium, potassium, and other valuable elements; Analyze, interpret, and synthesize experimental results to support process optimization; Contribute to the assessment of the environmental and sustainability performance of the developed processes; Prepare scientific publications, technical reports, and presentations; Candidate Profile: Required qualifications : PhD in chemical Engineering, biotechnology or related discipline. Proven experience in mineral characterization, liquid analysis and process development; Strong background in solution chemistry and bioprocessing; Excellent analytical and problem-solving skills; Strong scientific writing and communication abilities in English; Ability to work both independently and within a collaborative research environment. Application Documents: Interested candidates should submit the following documents: Cover letter Detailed CV List of publications Copies of diplomas Professional references (minimum of 2) 

Salary

Competitive

Posted

18 May 2026

ASARI - Postdoctoral Fellow in Plant Nutrition and Fertilization

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


Location: ASARI Institute, Mohammed VI Polytechnic University (UM6P), Laayoune, Morocco Position overview: The ASARI Institute at Mohammed VI Polytechnic University (UM6P) is seeking a highly motivated and skilled Postdoctoral Fellow in Plant Nutrition and Fertilization. The successful candidate will contribute to cutting-edge research aimed at developing sustainable soil fertility management systems for marginal agricultural soils, particularly under conditions of salinity and drought. The research will focus on the use of phosphate rock (RP) and its integration with diverse cropping systems, including legumes, cereals, grasses, and vegetables. The appointed candidate will conduct field, greenhouse, and laboratory trials, analyze data, and publish findings in high-impact journals. The role requires active participation in an interdisciplinary team to evaluate and optimize integrated soil fertility management strategies. Key duties and responsibilities: Research implementation: Design and conduct field, greenhouse, and laboratory experiments to evaluate the effectiveness of phosphate rock (RP) and other fertilization strategies in improving soil fertility and crop productivity. Investigate the interactions between soil amendments, cropping systems, and environmental stressors (salinity, drought) on plant nutrition and growth. Crop and soil analysis: Perform detailed analyses of plant tissues, soils, and fertilizers to assess nutrient uptake, soil health, and fertilizer efficiency. Use advanced analytical techniques to measure nutrient availability, soil microbial activity, and plant responses. Data management and analysis: Collect, manage, and analyze experimental data using statistical and modeling tools. Interpret results to draw meaningful conclusions and develop recommendations for sustainable agricultural practices. Publication and dissemination: Prepare high-quality research papers for publication in peer-reviewed journals. Present findings at national and international conferences, workshops, and seminars. Interdisciplinary collaboration: Work closely with a multidisciplinary team of scientists, agronomists, and environmental specialists to develop integrated soil fertility management systems. Collaborate with local and international partners to align research objectives with global sustainability goals. Project management: Contribute to the planning, execution, and reporting of research projects. Ensure timely delivery of project milestones and deliverables. Mentorship and training: Supervise and mentor PhD students and research assistants involved in the project. Provide training on experimental techniques, data analysis, and scientific writing. Requirements: Educational background: A Ph.D. in Plant Nutrition, Soil Science, Agronomy, Crop Science, or a closely related field. Research experience: Proven experience in conducting field, greenhouse, and laboratory experiments related to plant nutrition, soil fertility, and fertilization. Familiarity with marginal agricultural soils, particularly under salinity and drought conditions, is highly desirable. Technical skills: Proficiency in soil and plant analysis techniques (e.g., nutrient quantification, soil microbial assays). Experience with statistical software (e.g., R, SAS, SPSS) and data modeling tools. Knowledge of integrated soil fertility management and sustainable agricultural practices. Publication record: A good track record of publishing research in reputable, peer-reviewed journals. Interpersonal and communication skills: Excellent written and verbal communication skills in English (knowledge of French or Arabic is an advantage). Ability to work effectively in a multicultural, interdisciplinary team environment. Personal attributes: Highly motivated, organized, and detail-oriented. Strong problem-solving skills and a proactive approach to research challenges. Working conditions: The position is based at the ASARI Institute in Laayoune, Morocco, with potential fieldwork in marginal and desert agricultural regions. The initial appointment is for one year, with the possibility of extension based on performance and funding availability. Application Process: Interested candidates should submit the following documents: A detailed CV, including a list of publications. A cover letter outlining research interests, relevant experience, and motivation for applying. Contact information for at least three professional references. This position offers an exciting opportunity to contribute to innovative research in sustainable agriculture and soil fertility management, with the potential to make a significant impact on food security and environmental sustainability in marginal regions.

Salary

Competitive

Posted

18 May 2026

COLCOM - Postdoctoral Researcher in Multimodal Crop Analysis & Fertilizer Optimization

MOHAMMED VI POLYTECHNIC UNIVERSITY

Mohammed VI Polytechnic University

Morocco

institution

Mohammed VI Polytechnic University

Morocco


About the recruiter — UM6P Mohammed VI Polytechnic University (UM6P) is a research-and-innovation focused university in Morocco committed to African development. UM6P’s College of Computing (Benguerir & Rabat campuses) advances world-class research and education in Computer Science, fostering partnerships with industry and local stakeholders. Project summary (one line) Develop farmer-centric systems that fuse multi-modal remote sensing, soil and phenology data to enable crop classification and precise, customized fertilizer recommendations. Selection criteria (short) Required PhD (awarded or defended before start) in Computer Science, Remote-Sensing/Geoinformatics, Agricultural Data Science, or related field. Strong track record in remote-sensing imagery and/or time-series analysis and ML/DL for spatio-temporal data. Advanced Python skills and experience with ML frameworks and geospatial tools (e.g., PyTorch/TensorFlow, rasterio/GDAL). Ability to work independently and produce reproducible research outputs. Good English (written & oral) and willingness to collaborate with agronomists and partners. Preferred Postdoc or ≥2 years research experience after PhD; first-author publications in relevant journals/conferences. Experience with multimodal data fusion (optical/SAR/soil/phenology), satellite platforms (Sentinel/Landsat/GEE), and building reproducible pipelines. Field/ground-truth experience, agronomic knowledge, or fertilizer-recommendation systems. French/Arabic useful for local engagement. Application materials (required) Cover letter (fit with CropID + available start date). CV with links (ORCID, GitHub). Research statement (1–2 pages) with a 12–18 month plan. Up to 3 representative papers and links to code/datasets (if available). 2–3 referee contacts. Selection & timeline (brief) Shortlist based on research fit, technical skills, and interdisciplinarity. Top candidates invited for a technical interview covering past projects, a 6-month plan, reproducibility practices, and farmer-translation. Appointment: fixed-term (24 months), UM6P (Benguerir). References Moreno-Revelo, M.Y., Guachi-Guachi, L., Gomez-Mendoza, J.B., Revelo-Fuelagan, J. & Peluffo-Ordonez, D.H. (2021). Enhanced convolutional-neural-network architecture for crop classification. Applied Sciences, 11(9), 4292. Bhattacharya, S. & Pandey, M. (2024). PCFRIMDS: Smart Next-Generation Approach for Precision Crop and Fertilizer Recommendations Using Integrated Multimodal Data Fusion for Sustainable Agriculture. IEEE Transactions on Consumer Electronics.

Salary

Competitive

Posted

18 May 2026

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Subjects Taught at Otto von Guericke University of Magdeburg

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Arts and Humanities

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Business and Economics

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Computer Science

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  • Physics and Astronomy

Psychology

  • Psychology

Social Sciences

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  • Politics and International Studies
  • Sociology