Doctoral Candidate in Plant Proteomics, Bioinformatics, and Biology
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University: Technical University of Munich
Location: Munich
Department: Wissenschaftliches Personal / TUM School of Life Sciences
Supervisor: Christina Ludwig
Deadline: June 29, 2026
Position Overview
Technical University of Munich is offering a fully funded PhD opportunity within the Elite Network Bavaria-funded graduate college “The Proteomes that Feed the World.”
The doctoral project focuses on uncovering defense-associated peptides in crop species using advanced proteomics, bioinformatics, and plant biology approaches.
The research will be conducted at the Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS).
About the Graduate College
“The Proteomes that Feed the World” is an interdisciplinary doctoral program aimed at understanding crop proteomes and improving global food sustainability.
Main objectives include:
Training future leaders in science, industry, and society
Building expertise in:
Proteomics
Plant science
Bioinformatics
Project management
Scientific communication
Developing a proteome atlas of the 100 most important crop plants for human nutrition
The program includes collaborations with international academic and industry partners.
Research Project
The PhD project investigates bioactive peptides involved in plant defense mechanisms.
Research topics include:
Plant responses to:
Pathogen attacks
Heat stress
Water limitation
Discovery and characterization of plant peptides using:
Mass spectrometry-based proteomics
Omics technologies
Bioinformatics workflows
Expansion of peptide studies from:
Arabidopsis thaliana
to agriculturally important crops
The project aims to improve understanding of plant resilience and contribute to future crop improvement strategies.
Eligibility Criteria
Applicants should have:
An internationally recognized MSc degree in:
Plant Biology
Analytical Chemistry
Biochemistry
Omics-related fields
Related life science disciplines
Essential skills:
Understanding of biological and biochemical concepts
Experience with proteomics or omics experiments
Interest in mass spectrometry technologies
Desirable skills:
Data mining and integration
Statistical analysis using:
R
Python
Additional qualities:
Self-motivation
Responsibility and flexibility
Ability to work in interdisciplinary teams
Strong English communication and presentation skills
The program aims to recruit candidates typically from the top 10% of their academic cohort.
What the University Offers
Successful candidates will receive:
A 4-year PhD position (October 2026 – September 2030)
Salary according to German TV-L E13 scale
Access to state-of-the-art proteomics infrastructure
Interdisciplinary research environment
Collaboration with life scientists and bioinformaticians
Excellent academic and career development opportunities
Equal Opportunity
Technical University of Munich strongly encourages applications from women and supports equal opportunities for candidates with disabilities.
Required Application Documents
Applicants must submit:
Motivation letter (maximum one page)
Curriculum Vitae (CV)
Degree certificates and academic transcripts
Names and email addresses of two referees
All documents should be merged into a single PDF file.
Application Process
Applications should be sent via email to:
Christina Ludwig
Email: tina.ludwig@tum.de
Shortlisted candidates will first attend online interviews, followed by in-person interviews in Freising.
Expected start date: 1 October 2026
Additional Information
The project is hosted within the TUM School of Life Sciences and the Bavarian Center for Biomolecular Mass Spectrometry (BayBioMS), providing access to cutting-edge proteomics technologies and international research collaborations.
PhD Position in Electrical Engineering at Eindhoven University of Technology
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Host University: Eindhoven University of Technology (TU/e)
Department: Department of Electrical Engineering
Location: Eindhoven, Netherlands
Scholarship Type: Fully Funded PhD Position
Salary: €3,059 – €3,881 per month
Application Deadline: 21 June 2026
Study Level: PhD
Applications are now open for the PhD on Emulation Framework for Self-Aware Neuromorphic System-on-Chip Architectures 2026 at Eindhoven University of Technology (TU/e) in the Netherlands. This exciting PhD opportunity is part of the prestigious REACT Marie Skłodowska-Curie Actions (MSCA) Doctoral Network. The fully funded PhD position is designed for highly motivated international students who are passionate about neuromorphic computing, artificial intelligence hardware, embedded systems, and compute-in-memory architectures.
This PhD project focuses on developing advanced FPGA-based emulation frameworks for next-generation neuromorphic system-on-chip (SoC) architectures. Inspired by the human brain, neuromorphic computing enables ultra-low-power intelligent systems through event-driven computation and on-chip learning. The research aims to solve major challenges related to power consumption, latency, and memory bandwidth while supporting secure and energy-efficient AI acceleration for future edge-intelligent systems.
The Eindhoven University of Technology PhD program provides researchers with an opportunity to work in a highly innovative environment within Brainport Eindhoven, one of Europe’s leading technology hubs. PhD researchers will collaborate with interdisciplinary experts in artificial intelligence, integrated circuit design, computer architecture, and embedded systems engineering.
More Details About the TU/e PhD Position 2026
Host University: Eindhoven University of Technology (TU/e)
Department: Electrical Engineering
Country: Netherlands
Program Type: Fully Funded PhD
Research Area: Neuromorphic Computing and Compute-in-Memory Architectures
Employment Type: Full-time (1.0 FTE)
Duration: 4 Years
Monthly Salary: €3,059 – €3,881
Supervisor: Dr. Manil Dev Gomony
Deadline: 21 June 2026
Research Objectives
The selected PhD candidate will work on several cutting-edge research objectives, including:
Developing FPGA-based emulation and prototyping frameworks for neuromorphic SoC architectures.
Designing energy-efficient and scalable compute-in-memory (CiM) systems.
Investigating secure AI acceleration and side-channel resistant neuromorphic systems.
Implementing and benchmarking hardware architectures using simulation and prototype platforms.
Exploring adaptive processing mechanisms for next-generation embedded and edge AI systems.
Collaborating with interdisciplinary teams across AI, computer architecture, circuit design, and embedded systems.
Eligibility Criteria
Interested applicants must meet the following eligibility requirements for the Eindhoven University of Technology PhD position:
Applicants must hold a Master’s degree in Electrical Engineering or a related field.
Candidates should have excellent academic results.
Applicants must have knowledge of Digital or Mixed-Signal IC Design and Computer Architecture.
Strong programming and scripting skills in HDL languages such as Verilog or VHDL, along with Python or TCL, are required.
Experience with commercial EDA tools such as Cadence or Mentor Graphics is preferred.
Knowledge of neuromorphic architectures and low-power IC design will be an advantage.
Applicants must demonstrate strong research, analytical, and problem-solving skills.
Candidates should be able to work in interdisciplinary research teams.
Applicants must have English language proficiency at C1 level.
Candidates must not have resided or worked in the Netherlands for more than 12 months during the last 3 years before recruitment.
Applicants must not already possess a doctoral degree at the time of recruitment.
Benefits of the TU/e PhD in Netherlands 2026
The Eindhoven University of Technology offers excellent financial and professional benefits to selected PhD candidates.
Financial Benefits
Monthly salary ranging from €3,059 to €3,881.
Annual vacation allowance of 8%.
Year-end bonus of 8.3%.
Pension scheme and social benefits.
Paid maternity and parental leave.
Commuting, internet, and work-from-home allowances.
Tax compensation scheme (30% facility) for international candidates.
Academic and Professional Benefits
Opportunity to work in a leading international research university.
Access to state-of-the-art laboratories and research facilities.
Participation in the prestigious REACT MSCA Doctoral Network.
Collaboration with world-class researchers and industry experts.
Professional development and high-quality training programs.
Opportunity to gain teaching and mentoring experience.
International research exposure in one of Europe’s top technology regions.
Required Documents
Applicants must prepare the following documents before applying:
Cover Letter explaining motivation for applying (maximum one page)
Detailed Curriculum Vitae (CV)
List of publications (if applicable)
Official BSc and MSc degree certificates
Academic transcripts for all degrees
English language proficiency proof (if required)
Application Process
The application process for the Eindhoven University of Technology PhD position is online.
How to Apply?
Visit the official TU/e application portal.
Carefully review the eligibility criteria and project requirements.
Prepare all required application documents.
Submit your online application through the university portal.
Applicants must also apply through the REACT project website.
Ensure all documents are complete before submission.
Applications submitted via email or post will not be accepted.
Apply before the deadline to be considered for the position.
Application Deadline
The last date to apply for the PhD on Emulation Framework for Self-Aware Neuromorphic System-on-Chip Architectures 2026 at Eindhoven University of Technology is 21 June 2026.
Why Study at Eindhoven University of Technology?
Eindhoven University of Technology (TU/e) is one of Europe’s leading research universities known for innovation, engineering excellence, and industry collaboration. Located in Brainport Eindhoven, the university provides researchers with access to one of the world’s most advanced high-tech ecosystems. TU/e offers an inspiring international environment where students and researchers work together on cutting-edge technologies with real-world impact.
This fully funded PhD opportunity in the Netherlands is ideal for students interested in neuromorphic computing, artificial intelligence hardware, embedded systems, and energy-efficient computing technologies.
UCL Parkinson’s Disease PhD Studentship 2026 | UK
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Are you interested in pursuing a fully funded PhD in neuroscience and genetics in the United Kingdom? The University College London (UCL) Parkinson’s Disease PhD Studentship 2026 is an excellent opportunity for students passionate about neurodegenerative disease research. This funded PhD project focuses on Parkinson’s disease, hereditary spastic paraplegia, multiple system atrophy, and repeat expansion disorders using advanced long-read sequencing technologies.
The UCL PhD studentship is offered by the Queen Square Institute of Neurology and provides funded doctoral research opportunities for highly motivated students in genetics, neuroscience, molecular biology, and related medical fields. In this article, you will find complete information about the UCL Parkinson’s Disease PhD Studentship 2026, including funding details, eligibility criteria, research objectives, required qualifications, and the application process.
About the UCL Parkinson’s Disease PhD Studentship
University College London (UCL) is offering a fully funded PhD studentship/fellowship focused on investigating Parkinson’s disease (PD), hereditary spastic paraplegia (HSP), multiple system atrophy (MSA), and repeat expansion disorders (RED).
The research project will use cutting-edge genomic technologies, including long-read DNA and RNA sequencing, to identify disease mechanisms and discover new disease-related genes associated with neurodegenerative disorders.
The PhD project is supervised by leading researchers:
Prof John Hardy
Prof Henry Houlden
Dr Zhongbo Chen
Students will work within the UCL Queen Square Institute of Neurology and the National Hospital for Neurology and Neurosurgery in London.
UCL Parkinson’s Disease PhD Studentship 2026 Summary
Host Institution: University College London (UCL)
Department: Queen Square Institute of Neurology
Study Destination: London, United Kingdom
Degree Level: PhD
Funding Type: Fully Funded Studentship
Research Area: Neuroscience, Genetics, Neurodegenerative Diseases
Program Duration: 3–4 Years Full-Time
Start Dates: September 2026 and June 2027
Application Deadline: May 31, 2026
Research Focus Areas
The PhD studentship focuses on understanding the genetic and molecular causes of neurodegenerative diseases.
Main Research Topics
Parkinson’s disease (PD)
Multiple system atrophy (MSA)
Hereditary spastic paraplegia (HSP)
Repeat expansion disorders (RED)
Neurodegeneration genetics
Long-read DNA and RNA sequencing
Exome and genome sequencing analysis
The research aims to identify new disease genes, uncover disease pathways, and improve understanding of neurodegenerative disorders.
Research Objectives and Techniques
The selected PhD candidate will participate in a wide range of laboratory and genomic research activities.
Major Aims of the Project
Investigate Parkinson’s disease, multiple system atrophy, hereditary spastic paraplegias, and repeat expansion disorders using modern genomic techniques.
Define genetically characterized and uncharacterized disease phenotypes.
Re-analyze short-read exome and genome sequencing data.
Conduct long-read DNA sequencing and genomic analysis in genetically unresolved families.
Laboratory and Research Techniques
Students will gain hands-on experience in:
DNA extraction
RNA extraction
Fragment analysis
Exome sequencing
Genome sequencing
Long-read sequencing technologies
Bioinformatics analysis
Human biological sample handling
Brain tissue research
UCL PhD Studentship Funding Benefits
The UCL Parkinson’s Disease PhD Studentship provides generous financial support for eligible students.
Funding Coverage
Selected students will receive:
Year 1 stipend: £23,180
Year 2 stipend: £24,223
Year 3 stipend: £24,952
Full UK home PhD tuition fee coverage for three years
Total funded tuition fees: £19,780
Access to world-class research facilities
Training in advanced genomic technologies
Additional Benefits
Opportunity to work with internationally recognized scientists
Access to UCL’s long-read sequencing facility
Research experience at a leading neuroscience institute
Exposure to clinical and translational neuroscience research
Networking opportunities with experts in neurodegenerative diseases
Eligibility Criteria for UCL Parkinson’s Disease PhD Studentship 2026
To qualify for this UCL PhD studentship, applicants must meet the following requirements.
Nationality and Fee Eligibility
The studentship is open only to UK home fee students.
Applicants must hold a UK passport or meet UK home fee eligibility requirements.
Academic Requirements
Applicants should have:
A biological sciences, medical, genetics, neuroscience, or related degree
A minimum 2:1 Honours BSc degree or equivalent
Preferably an MSc with genetics, epidemiology, or laboratory experience
Alternatively, an MD or MBBS degree may also be suitable
Preferred Experience
Ideal candidates may have experience in:
Human brain tissue research
Biological sample handling
Laboratory genetics
Molecular biology
Genomic sequencing
Epidemiology research
Personal Qualities
Applicants should be:
Highly motivated
Able to work independently and in teams
Interested in neuroscience and genetics research
Passionate about neurodegenerative disease studies
Study Location
The PhD research will take place at:
UCL Queen Square Institute of Neurology
National Hospital for Neurology and Neurosurgery
Queen Square, London WC1N 3BG
Why Study at UCL?
University College London is one of the world’s leading research universities and is internationally recognized for excellence in neuroscience and genetics.
Advantages of Studying at UCL
Access to cutting-edge genomic research facilities
Collaboration with world-leading neuroscientists
Strong research environment in neurodegenerative diseases
Clinical research opportunities
Internationally recognized degree and research training
Location in central London with access to global scientific networks
Application Process for UCL Parkinson’s Disease PhD Studentship 2026
Follow the steps below to apply for the UCL Parkinson’s Disease PhD Studentship.
Step 1: Prepare Application Documents
Applicants should prepare:
Updated Curriculum Vitae (CV)
Academic transcripts and certificates
Relevant supporting documents
Step 2: Write an Application Email
Interested candidates must send an email expressing interest in the PhD studentship.
Step 3: Submit Application
Send your CV and application by email to:
Step 4: Await Further Communication
Shortlisted candidates may be contacted for interviews or further discussions.
Important Funding Notes
Funding covers UK home tuition fees only.
The fourth year is classified as Completing Research Status.
Additional studentships may also become available annually.
Research References and Background
The project builds upon internationally recognized research conducted by Prof John Hardy’s team, including:
Discovery of the APP gene in Alzheimer’s disease
Research contributing to the development of the drug Lecanemab
Identification of the PSMF1 gene pathway in Parkinson’s disease
These discoveries have significantly advanced the understanding of neurodegenerative diseases and treatment pathways.
Tips for a Strong PhD Application
Highlight laboratory and genetics experience.
Demonstrate strong academic performance.
Show interest in neurodegenerative disease research.
Mention sequencing or bioinformatics skills if applicable.
Tailor your CV to neuroscience and genetics research.
Apply before the deadline.
UCL Parkinson’s Disease PhD Studentship Deadline 2026
The deadline to apply for the UCL Parkinson’s Disease PhD Studentship is:
May 31, 2026
Applicants are encouraged to submit applications early.
Official Website
To learn more about the UCL Parkinson’s Disease PhD Studentship and related research activities, visit the official UCL and UK Dementia Research Institute websites.
PhD Research Fellow in Global Development and/or Planning
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University: University of Agder
Location: Kristiansand (Campus Kristiansand)
Department: Global Development and Planning
Supervisor: Arnhild Leer-Helgesen
Deadline: 1 August 2026
Salary: NOK 550,800/year
Position Overview
University of Agder is offering 1–3 PhD Research Fellow positions in the Department of Global Development and Planning for a 3-year (or 4-year with teaching duties) doctoral programme.
The position is interdisciplinary and focuses on global development, planning, and critical social sciences.
Research Themes
Applicants must align their PhD project with at least one of the following themes:
1. Contested Energy Transitions
Focuses on:
Low-carbon and renewable energy transitions
Conflicts over land use, governance, and justice
Power relations in energy infrastructure
Community participation and democratic decision-making
Environmental and social impacts of energy systems
2. Reimagining and Repoliticizing Planning
Focuses on:
Planning as a political (not neutral) process
Power structures in urban and regional planning
Smart cities, sustainability, and digitalization as political constructs
Role of media, art, and communication in planning
Marginalized communities and counter-hegemonic practices
3. Challenges and Alternatives in a Polarized World
Focuses on:
Inequality, climate crisis, conflict, and political polarization
Gendered and intersectional impacts of crises
Youth-driven social change in the Global South
Human rights, democracy, and resistance strategies
Alternative development pathways in crisis contexts
Eligibility Criteria
Applicants should have:
A Master’s degree (120 ECTS) in social sciences or related fields
Minimum grade B average or equivalent
Strong English language skills (written and spoken)
A strong and original PhD project proposal
Applicants in final stages of their Master’s degree may also apply (degree must be completed within 4 weeks after deadline).
Desired Qualifications
Research experience or academic publications
Teaching experience at university level (preferred)
Strong analytical skills
Ability to work independently and collaboratively
High academic motivation and engagement
Experience in research projects is an advantage
Personal Qualities
The university values candidates who are:
Independent and organized
Strong communicators
Collaborative and open-minded
Academically motivated and proactive
Interested in teaching and academic development
Employment Conditions
Full-time PhD position (3 years, extendable to 4 years with teaching duties)
Located at Campus Kristiansand
Salary: NOK 550,800 per year
Membership in the Norwegian Public Service Pension Fund
Inclusive and international working environment
Opportunities for professional development
Application Requirements
Applicants must submit:
Certificates and academic transcripts
Master’s thesis
CV and list of publications
References
Research project description (max 7 pages, including references)
Other relevant academic work
Application Process
Applications must be submitted electronically via the university portal before:
Deadline: 1 August 2026
Shortlisted candidates will be invited for interviews, and reference checks may be conducted.
Contact
Head of Department: Arnhild Leer-Helgesen
Email: arnhild.leer-helgesen@uia.no
Research Associate Position in Contrastive Learning and GeoAI
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University: Technical University of Munich
Location: Munich
Department: Wissenschaftliches Personal / Professorship Big Geospatial Data Management
Supervisor: Martin Werner
Deadline: July 31, 2026
Position Overview
Technical University of Munich is offering a Research Associate position in the field of Contrastive Learning and GeoAI within the Professorship of Big Geospatial Data Management.
The project is funded by the German Research Foundation (DFG) and focuses on advanced machine learning techniques for geospatial applications.
The position also provides the opportunity to pursue a doctoral degree.
About the Research Group
The Professorship of Big Geospatial Data Management specializes in:
Acquisition and analysis of geospatial data
Distributed computing
Machine learning
Computer vision
Image and text analysis
High-performance computing
Quantum algorithms
Visualization of large-scale georeferenced datasets
The group supports computational thinking and data-driven Earth science research.
Research Project
The project focuses on:
Hard negative sampling for contrastive representation learning
Developing domain-aware sampling strategies using:
Spatial distance
Sensor metadata
Existing maps
Investigating coreset selection methods for large geospatial datasets
Application areas include:
Cross-view geo-localization
Visual place recognition
Aerial imagery analysis
Street-view imagery
LiDAR data processing
The research combines machine learning, geospatial intelligence, and computer vision techniques.
Responsibilities
The selected candidate will:
Conduct research related to the project themes
Develop innovative solutions proactively
Publish research findings in peer-reviewed journals and conferences
Present research at scientific events
Contribute to broader GeoAI and machine learning research activities
Eligibility Criteria
Applicants should have:
A completed Master’s degree in:
Computer Science
Mathematics
Physics
Geoinformatics
Data Science
Related disciplines
Required skills:
Strong background in machine learning
Excellent programming skills in:
Python
C++
Related technologies
Ability to work independently
Strong willingness to learn new techniques
Fluent English communication skills
Preferred qualifications:
Experience with:
Contrastive learning
Computer vision
Geospatial datasets
GeoAI research
German language skills are considered an advantage.
Employment Benefits
The position offers:
Full-time employment (100%)
TV-L E13 salary scale
Three-year contract
Opportunity to pursue a PhD degree
Access to modern research infrastructure
International research environment
Collaboration opportunities with industry and research institutes in Munich’s “Space Valley” ecosystem
Application Documents
Applicants should submit:
Motivation letter
Curriculum Vitae (CV)
Degree certificates and academic transcripts
Employment certificates
Other relevant supporting documents
All documents should be combined into a single PDF file.
Application Process
Applications should be sent via email to:
Applications must be submitted no later than 1 August 2026.
Expected starting period: September to November 2026
Equal Opportunity
Technical University of Munich encourages applications from women and gives preference to candidates with disabilities when qualifications are equivalent.
Contact Information
Professorship Big Geospatial Data Management
Technical University of Munich
Supervisor: Martin Werner
Location: Ottobrunn, Germany
Email: applications.bgd@ed.tum.de