Digital transformation, Lean Manufacturing and management, Production systems, Smart Factory.

aleksandar.argilovski@mf.edu.mk 

Borjana Arsova is a co- group leader of the Root Dynamics Group in the Plant Sciences Institute in the research center in Julich, Germany. She graduated with a PhD in biochemistry at the Max-Planck Institute of Molecular Plant Physiology and the University of Potsdam in Germany, after which she was an independent researcher in the University of Düsseldorf (Germany) and the University of Liege (Belgium). 

Throughout her career she worked on protein post-translational modifications and protein related signaling processes with major focus on plant nutrient uptake and nutrient sensing and signaling. Her current research direction involves linking plant phenotype with understanding of the underlying molecular processes (phenomics) using invasive and non-invasive phenotyping. The projects aim at improving plant performance at limiting growth conditions particularly via the use of beneficial microbes. Her group works at the interface of lab and field, linking research and application in agriculture.

She is interested in connecting with, and establishing collaborations with Macedonian scientists on related topic. She can also advise young Macedonian researchers and students during the process of writing applications to secure funding for research in her group.

Website: https://www.fz-juelich.de/en/ibg/ibg-2/forschung/research-groups/root-dynamics

Contact: borjana.arsova@gmail.com

Aleksandar Bojchevski is a tenured professor of Computer Science at the University of Cologne where he leads the research group on Trustworthy Artificial Intelligence. Broadly speaking his research is about models and algorithms that are not only accurate or efficient but also robust, uncertainty-aware, privacy-preserving, fair, and interpretable. One focus area of his research is (trustworthy) graph-based models such as graph neural networks. Previously he was faculty at the CISPA Helmholtz Center for Information Security. Before that he did a PostDoc and completed his PhD on machine learning for graphs at the Technical University of Munich, advised by Stephan Günnemann.

There are several open positions in his research group on a variety of trustworthy machine learning topics.

Website: https://abojchevski.github.io/

Contact: aleksandar.bojchevski@gmail.com

Jacob Chakareski is an Associate Professor in the College of Computing at the New Jersey Institute for Technology (NJIT), where he holds the Panasonic Chair of Sustainability and directs the Laboratory for AI-Enabed Virtual and Augmented Reality Immersive Communications and Networked Systems. His research interests span next generation virtual and augmented reality systems, UAV IoT sensing and networking, fast reinforcement learning, 5G wireless edge computing and caching, ubiquitous immersive communication, NextG XR network systems and societal application, domain aware reinforcement and deep learning. He received the Adobe Data Science Faculty Research Award in 2017 and 2018, the Swiss NSF Career Award Ambizione (2009), the AFOSR Faculty Fellowship in 2016 and 2017, and Best Paper Awards at ICC 2017 and MMSys 2021. He completed his Ph.D. degree at Rice and Stanford in Electrical and Computer Engineering, held research appointments with Microsoft, HP Labs, and EPFL, and served on the advisory board of Frame, Inc. His research has been supported by the NSF, NIH, AFOSR, Adobe, Tencent Research, NVIDIA, and Microsoft. 

He has multiple openings in his lab and is looking forward to connecting with researchers from Macedonia.

Website: http://www.jakov.org

Contact: jacobcha@njit.edu

Angjela Davitkova is a researcher in the group of Sebastian Michel, who is interested in recruiting other Macedonian students for internship/mentorship. 

Website: https://dbis.informatik.uni-kl.de/index.php/en/people/michel

Contact: davitkova@cs.uni-kl.de

vesna.dimitrievska@silicon-austria.com 

Rozita Dimova, PhD (Stanford, 2004) is a Social Anthropologist with a distinguished record of achievements, including the prestigious Robert Texture Award for Outstanding Creativity in Anthropology. Rozita has held research and teaching positions at prominent institutions, including the Max Planck Institute for Social Anthropology in Halle (2003-2006), Free and Humboldt Universities in Berlin (2007-2015), Associate Professorship in Southeast European Studies at Ghent University in Belgium (2013-2020) and Senior Fellowship at the Institute for Advanced Studies in Kőszeg, Hungary. Her research portfolio includes materiality, consumerism and aesthetics, ethno-nationalism, borders and refugee studies. A prolific author, Rozita is notable for her monographs, Ethno-Baroque: Materiality, Aesthetics, and Conflict in Modern-day Macedonia (Berghahn, 2013) and Border Porosities: Movements of People, Objects, and Ideas in the Southern Balkans  (Manchester University Press, 2021). 

roz.dimova@gmail.com 

Individual research fellowships is available at the Institute for Advanced Studies in Kőszeg, Hungary. 

https://iask.hu/en/call-for-application-for-individual-research-scholarships-at-iask-2024/ 

Ilija Dukovski is a research assistant professor in the Bioinformatics Program at Boston University in the USA. He completed his studies in theoretical physics at the University of Belgrade, Serbia, and he received his doctorate from the University of Massachusetts in Amherst, USA, in the field of statistical physics. After his postdoctoral studies in the field of polymer physics, and working in the, Ilija joined Daniel Segre's lab (https://www.bu.edu/segrelab/) at Boston University.

These days he is engaged in research in systems biology and biophysics of multicellular aggregates, such as bacterial biofilms, microbial communities and microbiomes, and tumors. Ilija is interested in cooperation in the field of making models for simulations of the development of multicellular aggregates and communities. His research is based on stoichiometric models of cellular metabolism at the level of the total genome of organisms. Ilija manages the development of the COMETS program which serves for simulations of the development and growth of bacterial colonies and biofilm (https://www.runcomets.org/). COMETS is open source software (https://github.com/segrelab/comets), and any collaboration is welcome in order to build a community of users and contributors.

One of the projects for which Ilija is currently developing models and simulations is mCAFEs (https://mcafes.lbl.gov/), a multi-institutional project whose team includes a Nobel Prize winner, and whose goal is to develop mechanistic and spatial-temporal knowledge of microbial interactions in plant root communities.

Another project that Ilija is involved with is the creation of simulations for researching the mechanisms of the formation of complex shapes in bacterial colonies (https://iopscience.iop.org/article/10.1088/1478-3975/ac8514).

Soon, Ilija will start a project to investigate the morphology and spatial diversity in tumors. The models for this project will be based on the human genome. If you are interested in cooperation, consultation or just a chat without any obligations regarding his research, write to Ilija at dukovski@bu.edu.

I am happy to announce the availability of a Marie Curie postdoc position at the Department of Knowledge Technologies of the Jozef Stefan Institute in Ljubljana. The postdoc position is part of a Marie Sklodowska Curie Activity (MSCA), titled Machine Learning for Science and Humanities (SMASH). This position is available to PhD holders with experience in Computer Science and Artificial Intelligence: The successful applicant will have the opportunity to join a team of world leading experts in the field.

The position is funded jointly (under the COFUND scheme) by the European Union and the Slovenian government for a two-year period. During this time, the post-doc will have access to the institute's resources, including state-of-the-art facilities and equipment, interdisciplinary research opportunities, and participation in career development activities. Thanks to Marie Curie funding rules, the post-doc will have a very competitive salary (roughly twice the salary of a postdoc funded according to local funding rules).

We are looking for an enthusiastic and highly motivated individual who is passionate about their research and eager to contribute to the institute's research on machine learning for science. The successful applicant will have a PhD, preferrably in Computer Science or Artificial Intelligence, and a strong interest in developing and/or applying machine learning and artificial intelligence methods to challenging scientific problems. If you are interested in this position, please contact Saso.Dzeroski@ijs.si as soon as possible: The deadline for appications is April 15, but applications need to include a short research project proposal aligned with the host's interests, so early contact is essential .

More information on the SMASH activity and how to apply for the postdoc position can be found at https://smash.ung.si/open-call-1/ The position at the  Department of Knowledge Technologies of the Jozef Stefan Institute falls under topic/research area 1 (Machine Learning for Scientific Applications), subtopics 1.1. (Learning from complex data and computational scientific discovery) and 1.3 (Beyond supervised leaning). I'm sure this is an exciting opportunity for young researchers interested in this field, so don't hesitate to contact me and apply! 

Ljupcho Efremov is Assistant Professor at American University of the Middle East in Kuwait where he teaches Psychology and Soft Skills. His professional interests are in the area of Business Psychology and Organizational Safety Climate. 

ljupco.efremov@gmail.com 

Kiril Gashteovski is a researcher at NEC Labs in Germany. His group has an opening for an internship that can lead to a Master's thesis.

Announcement: https://jobs.neclab.eu/jobs/openings/students/NEC-NLE-2301-113-GML-2-Internship_on_Information_Extraction_on_Materials_Science_Documents_%5b2023-01-113-GML%5d.pdf

Contact: kiril.gashteovski@gmail.com

We offer short-term MSc scholarships for computer science students: https://www.usi.ch/en/feeds/24231 

martin.gjoreski@usi.ch 

Irena Ivanovska is a Scientific Collaboration Director at the Belfer Office for Dana-Farber Innovation at the Dana-Farber Cancer Institute. Irena has a depth of experience in the biotech and pharmaceutical industries as well as in non-profit. She was a Senior Scientific Director at The Mark Foundation for Cancer Research, where she led several grant programs and was instrumental in shaping the Foundation’s strategic priorities. Prior to that, Irena was the Site Head for Celdara Medical, Boston where she expanded the company into the Boston/Cambridge biotech ecosystem, led pipeline development at this unique biotech focused on advancing academic research toward and into the clinic, and directed preclinical research for small and large molecule therapeutics in oncology and infectious disease. Before joining Celdara, Irena led R&D teams at Merck & Co., Inc., in oncology and autoimmune diseases, developing small molecule and RNA-based therapeutics. Irena received a PhD in Molecular Biology from Princeton University (yeast genetics) and completed her postdoctoral training at the Whitehead Institute (Drosophila meiosis). She serves as a mentor to young scientists and budding entrepreneurs informally and is part of several Massachusetts based mentoring programs at MassBio, WEST, MGH Postdoc Association, and Nucleate. She is a lead- and co-author on multiple scientific papers in diverse disease areas. Irena is a mom to a delightful 8-year old daughter. 

irenaivan@gmail.com

aleksandar@kondinski.com 

irinakotlar87@yahoo.com 

I am a PhD student at the University of Bern at the Institute of Archaeological Sciences. My research focus are dendrochronology, radiocarbon dating and modelling, wood anatomy, and ultimately a precipitation reconstruction based on tree-rings from prehistoric archaeological sites in Macedonia, Albania and Greece. 

We don't currently offer any position at my institute.

However, there are scholarship opportunities for foreign students interested in pursuing a postgraduate degree  at any Swiss University offered by the Swiss Government (for doctoral or post-doctoral research). For example there is the Swiss Government Excellence Scholarship, for which one of the requirements is having a host professor at a Swiss University. I am not involved in any way with these scholarships nor the granting body, however I could potentially help interested candidates find relevant host professors at the University of Bern in the areas of archaeology, paleoecology, paleoclimate. Info on these scholarships: 

https://www.eda.admin.ch/countries/north-macedonia/en/home/news/news.html/content/countries/north-macedonia/en/meta/news/2023/August/Swiss_Government_Excellence_Scholarships_for_Foreign_Scholars_for_the_2023-2024_Academic_Year

andrej.maczkowski@unive.ch 

Psychology of moral, political psychology, virtual communication, Interpersonal communication, Mass media, Gestalt psychotherapy, EMDR. 

marijana@isppi.ukim.edu.mk 

Ljupcho Milosheski is a PhD student working at the intersection of deep learning and spectrum analysis, devising algorithms that can automatically identify and categorize spectrum patterns without the need for labeled data. He co-authored 1 journal and 2 peer reviewed conference papers and is also involved in the HE NANCY project. He is enrolled at the International Postgraduate School Jožef Stefan and working with the department of Communication Systems at the Jožef Stefan Institute. He received the MSc degree from the Faculty of Electrical Engineering and Information Technologies in Skopje, Macedonia.  

ljupcho.milosheski@ijs.si 

At the Communications Systems Department of the "Jožef Stefan" Institute, in collaboration with the ComSensus company, we are looking for a doctoral candidate to conduct research in the field of smart grid management using artificial intelligence in a mixed academic and industrial environment. Special attention will be given to algorithms in the field of Deep Reinforcement Learning. The development of the system will also require the candidate to gain an in-depth understanding of mobile telecommunication systems, energy smart grids, and modern techniques for managing radio and network resources in wireless networks. The candidate will use various algorithms for regression and time series classification and methods for adapting these algorithms in networks. They will also work closely with the young deep tech company ComSensus in designing and conducting experiments, data analysis, and deep learning model development on experimental setups.

We are looking for a curious person who is ready to continuously acquire new knowledge and face the challenges of modern technology. It is important that you are interested in research and development work and have the ability to solve problems without constantly needing direction. We also value good communication, both written and oral, in English, as it contributes to successful collaboration in an international environment. Good knowledge of programming in Python, basics of artificial intelligence, data analysis, and ICT systems is an added advantage. Additionally, we expect proactive team participation, where you can regularly present your ideas to colleagues, assist in leading student projects, and contribute to our shared GitHub repository.

The work program will be designed so that during doctoral studies, the candidate will become an independent researcher with experience in direct collaboration in an industrial environment. Special emphasis will be placed on gaining various international experiences in the form of internships and short-term research visits, as well as opportunities to participate in research projects funded by the EU and conducted within the expanded research group. The research findings will be published at representative international scientific conferences and in international journals with an impact factor, and at the end of the doctoral studies, the findings will be summarized in a doctoral dissertation.

Estimated salary: 1800-2200 Gross + meal and transport allowance, annual bonus. With successful work, there's also the possibility of additional performance-based rewards, which can be up to 20% of the gross salary.

Other benefits: Tuition and enrollment fees for doctoral studies, payment of registration fees and trips to international conferences, opportunities for further training, and working with top-notch research equipment.

We invite students who have completed a second-level university degree in computer science, mathematics, or other natural-technical disciplines to join our team at SensorLab laboratory. Please send your resume in the Europass style or similar to sensorlab@ijs.si. For more information, contact Jernej Hribar (jernej.hribar@ijs.si).

The call is open until the position is filled, with priority given to candidates who can start their doctoral studies in the academic year 2023/24. 

Panče Naumov is a tenured professor at the Division of Science and Mathematics, New York University Abu Dhabi (NYUAD), and a Global Network Professor of Chemistry at the Faculty of Arts and Sciences, New York University, with a cross-appointment at New York University’s Molecular Design Institute, a Director of the NYUAD Center for Smart Engineering Materials (CSEM) and a leader of the Smart Materials Lab (SML) at NYUAD. He also is a former fellow of the Radcliffe Institute at Harvard University. The Naumov Smart Materials Lab is the leading research team in chemistry and materials science in the UAE with an output, according to Nature Index, that accounts for about 40-60% of the high-impact publications in chemistry in the country each year.

Link to full bio:

https://nyuad.nyu.edu/en/academics/divisions/science/faculty/pance-naumov.html

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The Smart Materials Lab (SML) and the Center for Smart Engineering Materials (CSEM) at New York University Abu Dhabi are inviting applications for a funded internship in the areas of chemistry, materials science and mechanical engineering with interests in smart materials, biomimetic and bioinspired materials, surface science, solid-state chemistry, microscopy, macro/micro/nanodevices, photochemistry, and photophysics. The lab is well equipped with state-of-the-art facilities for X-ray diffraction, spectroscopy, microscopy, thermal and mechanical materials characterization, and organic synthesis. Moreover, the intern will have access to the well-equipped core research facilities of NYUAD.

Priority will be given to candidates with a background in the following primary and secondary areas of expertise:

(1) Mechanical engineering: Mathematical modeling, tracking and analysis of motion, experience with finite element analysis, analysis of bending and twisting beams

(2) Solid-state physics: Analysis of inorganic or organic crystalline solids, characterization of their mechanical properties, modelling of deformations and defects in solids

(3) Bio-related materials: Biomimetic and bioinspired materials

(4) Devices: Design, fabrication and testing of small mechanical devices, experience with working in a clean room, microfluidics, experience with automated sampling and chemical analysis

(5) Surface and colloid chemistry: Experience with using quartz crystal microbalance, chemical and physical characterization of colloids, small-angle scattering and diffuse scattering

(6) Microscopy: Advanced methods of atomic force microscopy in solid and liquid state, scanning electron microscopy in non-atmospheric conditions, TEM of organic materials  

(7) Organic synthetic chemistry: Design of synthetic pathways to new small molecules and polymers and complete characterization by using NMR and other spectroscopic methods.

Link to the SML:

https://nyuad.nyu.edu/en/research/faculty-labs-and-projects/smart-materials-lab-sml.html

Link to the CSEM:

https://nyuad.nyu.edu/en/research/faculty-labs-and-projects/center-for-smart-engineering-materials.html

My research falls on the intersection between social networks, social psychology and organizational behavior. I am particularly interested in understanding how interpersonal relations (such as friendship, avoidance, communication) emerge, how they subsequently impact outcomes (such as individuals’ innovative behavior, well-being), and how these relations and outcomes coevolve over time. 

vojkan.nedkovski@unimi.it 

Interested in cooperation with research institutions that work in the field of sheep and goat selection, that is, the selection of domestic animals. Specifically providing advanced software to control production and reproductive traits in sheep and goats. 

npacinovski@yahoo.com 

Marina Panova-Noeva, MD, MSc, PhD is a group leader in the field of clinical epidemiology at the University Medical Center Mainz in Germany. Dr. Panova-Noeva finished her Medical studies and specialization in Internal Medicine at the University "Ss Cyril and Methodius" in Skopje, Macedonia. She completed her Master of Science degree at Karolinska Institute in Stockholm, Sweden and her Ph.D. degree at the Maastricht University in the Netherlands. She is interested in long-distance mentoring of Macedonian students. More information on Dr. Panova-Noeva's research interests are available at: https://www.unimedizin-mainz.de/cth/professorships-work-groups/dr-panova-noeva.html?L=1

Contact: mpanova@yahoo.com

Young researcher position is available at the Laboratory for Open Systems and Networks, Institute Jozef Stefan - Ljubljana.

 Information about the position and the application process can be found here: https://mr.ijs.si/en/tender/#tender

atanja@e5.ijs.si 

Andrej Risteski (https://www.andrew.cmu.edu/user/aristesk/)  is an Assistant Professor in the Machine Learning Department at Carnegie Mellon University. Prior to joining Carnegie Mellon, he was the inaugural Norbert Wiener Research Fellow jointly in the Applied Math department at MIT, and the Institute for Data Science and Statistics (IDSS). He received his PhD in Computer Science in Princeton University under the advisement of Sanjeev Arora, where he also received his Bachelor's degree in Computer Science.  

His broad area of research concerns mathematical and scientific foundations of machine learning and artificial intelligence, with a particular focus on deep learning and neural networks. He publishes in flagship conferences for machine learning, like NeurIPS, ICML and ICLR, as well as flagship theoretical computer science conferences like STOC and COLT. His research is funded by the NSF (IIS-2211907) and an Amazon Research Award (“Causal + Deep Out-of-Distribution Learning”).

His topics of current interest include generative models, self-supervised and representation learning, designing and analyzing algorithmic tools for learning and inference using stochastic differential equations, robustness and out-of-distribution generalization, and applications of neural approaches to natural language processing and scientific domains. For a list of recent publications, visit his website:

https://www.andrew.cmu.edu/user/aristesk/

Professor Risteski invites applications for new collaborations and remote advising, with the potential for a funded visit in the future. The nature of Professor Risteski’s work allows for remote work— e.g., brainstorming for new projects, collaborations with students in his group, as well as access to his compute. Priority will be given to students with a strong mathematical background, particularly in high-dimensional probability, linear algebra, calculus, and theoretical computer science. Experience with deep-learning-related tools (PyTorch, Colab, Wandb, …) is a plus. 

For contact, email Professor Risteski at aristesk@andrew.cmu.edu

Simona Samardjiska is an assistant professor in the digital security group at Radboud University. She encourages students to reach out to her if they are interested in doing research in post-quantum cryptography.

Website: https://samardjiska.org/

Contact:  simonas@cs.ru.nl

Martin Saveski is an Assistant Professor at the University of Washington Information School. He received his Ph.D. from the Massachusetts Institute of Technology and was a Postdoctoral Scholar at Stanford University. His research develops tools for analyzing large-scale social data, aiming to provide a better understanding of social structure and behaviors online while also impacting the design of digital social systems. His recent work has focused on reducing political polarization online, improving the quality of online conversations, and causal inference in social systems. His research often falls at the intersections of Social Networks, Machine Learning, and Causal Inference. His work typically appears in venues such as ICWSM, WWW, and KDD, and has included collaborations with researchers at Twitter, Facebook, and LinkedIn. His research has been awarded a best paper honorable mention at WWW ’18 and has been featured in popular media outlets, including The New York Times, NPR, and the MIT Tech Review.

Martin is looking for students with a background and/or interest in social network analysis, machine learning, causal inference, or natural language processing, and are passionate about using computational methods to study how online social platforms can be reimagined to enable better conversations, bridge political divides, and reduce the spread of misinformation.

Website: http://martinsaveski.com/

Aleksandar Shulevski is an instrument scientist at ASTRON, the Netherlands Institute for Radio Astronomy. Previously, he was a researcher at Leiden University, researcher and project scientist at the University of Amsterdam, and support scientist at ASTRON. He completed his astrophysics BSc and MSc degrees at Leiden University and his PhD at Groningen University. He also holds a BSc in electrical engineering (electronics and telecommunications track) from the Faculty of Electrical Engineering (ETF, now FEIT) at the University Ss Cyril and Methodius in Skopje, Macedonia.

He is interested in collaborating with junior researchers from Macedonia, as well as helping Macedonia develop research infrastructure by collaborating with universities / institutions abroad, especially in the Netherlands.

Website:  https://www.astron.nl/~shulevski/
Contact: a.shulevski@gmail.com

Соработка со УКИМ за размена на студенти на краток временски период (3-6 месеци на пракса, магистерска работа или сл.). Студентите би работеле на проекти од областа на астрономија и ќе работат на научни истражувања со податоци од вселенските телескопи Џејмс Веб и Хабл. Студентите со својата работа несомнено ќе бидат во листата на автори на релевантни трудови во најголемите астрономски списанија а во најдобар случај и први автори (со дополнителна работа на подолг период). Во моментов, би сакал да ја разгледам можноста за ваква соработка од аспект на финансирање на престојот на студентите во Копенхаген. 

markoshuntov@gmail.com 

Experienced Associate Professor with a demonstrated history of working in the higher education industry. Skilled in ornamental trees and shrubs, woody plant ecology, invasive alien plants, lecturing, research. Strong education professional with a Doctor of Science (Dr.sc) focused in phytosociology, and Master of Science (M.Sc.) focused in dendrology from Ss. Cyril and Methodius University in Skopje, Hans Em Faculty of Forest Sciences, Landscape Architecture and Environmental Engineering.

Assoc. Prof. Dr.sc Simovski helds two courses both in Macedonian and English language: Urban Dendrology (first cycle of studies), and Urban Dendrology 2 (second cycle of studies), classes which all interested international students can choose as an elective, of course according to their home institution study programmes. These courses focus mainly on morhological and ecological features of native and exotic woody plants that can be used in cities.

Likewise, he is involved in selection of woody species suitable for landscaping of peri-urban sites and industrial/anthropogenic environments. In the past couple of years, he is investigating in particular suitability of certain native drought-resistant woody plants for landscaping/afforestation of (thermo-)xeric sites.

bsimovski@sf.ukim.edu.mk 

Prof. Nikola Stikov is associate professor of biomedical engineering, a researcher at the Montreal Heart Institute, and co-director of NeuroPoly, the Neuroimaging Research Laboratory at École Polytechnique, University of Montreal. Prior to joining the Polytechnique faculty, Prof. Stikov completed his postdoctoral training at the Montreal Neurological Institute, and his B.S., M.S., and Ph.D. degree at Stanford University.  Prof. Stikov's research runs the gamut of quantitative magnetic resonance imaging, from basic issues of standardization and accuracy, to biophysical modeling, microstructural imaging and clinical applications. He is a vocal open science advocate, sitting on the steering committee of the Canadian Open Neuroscience Platform (CONP) and the Quebec Biomaging Network (QBIN). He is also co-founder of NeuroLibre.org, a preprint server for hosting executable research objects, and a research fellow at the Center for advanced interdisciplinary research at the University Ss Cyril and Methodius in Skopje, Macedonia.

Prof. Stikov is interested in collaborating with junior researchers from Macedonia, and he has openings for an internship at the University of Montreal. He is also funding Macedonian researchers to develop interactive research objects through his NeuroLibre project.

Call for interactive visualisations:  https://forms.gle/wBCpjAb3EWVZapXi6
Contact e-mail address: nikola.stikov@polymtl.ca

I'm a doctoral researcher at Ghent University. My research focuses on the internationalisation of Higher Education in Small States. My research interests also include: Policy, Governance and Management in Higher Education; Sustainable development goals and Higher Education; Higher Education and International Organizations. If there are other researchers interested in or working on some of these areas, I'd really appreciate the chance to connect with them and discuss possible research projects and papers. 

Biljana.KuzmanovskaTasetovikj@ugent.be 

ntrpcevska@gmail.com