Trakia University

Times Higher Education

Overview

For Students

For Professionals

Basic information and contact details for Trakia University

About Trakia University

Contact Trakia University

Build your profile to connect with students and professionals around the world

Do you work for this institution?

No Poverty

Zero Hunger

Good Health and Wellbeing

Quality Education

Affordable and Clean Energy

Industry, Innovation and Infrastructure

Peace, Justice and Strong Institutions

Partnership for the Goals

Overall

World University Impact Rankings - Clean Energy 2024

Select the type of ranking below to see stats

Impact Rankings

About

Rankings

Key stats

Jobs

Subjects

Downloads

FAQs

Suggested universities

New Zealand, Auckland

Job Description


	Seeking a truly collaborative leader in brain research who will engage research, clinical and related communities in a vision for developing a better understanding of the human brain and for improving outcomes for those affected by brain disorders.
	Live and work in New Zealand’s largest, most cosmopolitan and culturally diverse city.


The University of Auckland, Waipapa Taumata Rau, has ambitious and transformative goals to deliver top quality research and impact both locally in the Pacific region and globally.

Join us in the substantive academic position of David Levene Foundation Chair in Brain Research, and apply your leadership to ensure the next horizon of success of the Centre for Brain Research Te Huinga Hinengaro (CBR). The director (appointed on an initial 5-year term) will build on CBR’s success in developing a strong and diverse community of neuroscience scholars who seeking to understand the human brain and to develop and translate therapies and other treatments for those affected by brain disorders.

CBR is one of seven transdisciplinary University Research Centres spanning multiple faculties, disciplines and academic activities and engaged in research with the community.

Established 15 years ago, effective relationships are at the heart of its reputation as a leader in translational brain research, as demonstrated by the philanthropic and community support it values dearly.

Members of the CBR are engaged in internationally recognised research ranging from basic and laboratory science to clinical research and the promotion of population health and research that works with and through engagement with communities, particularly Māori and Pacific communities. Creating stronger ties among scientists, engineers, clinicians, potential industry partners and the community, whilst training the next generation of leaders in the field will be central to the Director’s aspriations for the CBR.

Learn more about CBR’s cutting edge research and world-class facilities, and review the position description here.

For further information and a confidential conversation, please contact Clare Litten, Manager, Academic Executive Search Service, c.litten@auckland.ac.nz

Applications must be submitted online, by the closing date of 9 March 2025

Additional Information

Equity

The University is committed to meeting its obligations under the Treaty of Waitangi and achieving equity outcomes for staff and students in a safe, inclusive, and equitable environment.  For further information on services for Māori, Pacific, women, LGBTQIATakatāpuiMVPFAFF+, people with disabilities, parenting support, flexible work and other personal circumstances go to www.equity.auckland.ac.nz

The University is committed to providing a safe, inclusive, and equitable environment where everyone can thrive. For further information see Te Ara Tautika | the Equity Policy and visit www.equity.auckland.ac.nz


The University of Auckland

United Kingdom, Glasgow

Closing date: 27/01/2025
Salary Range: £32,296 - £33,882
FTE: 1 (35hours/week)
Term: Fixed (6 months)

We are seeking a Research Assistant to work in the marine modelling group of the Department of Mathematics and Statistics. The successful candidates will join our team working on applying and extending the scope of the StrathE2E marine ecosystem model for regions of the Atlantic Ocean (https://outreach.mathstat.strath.ac.uk/apps/StrathE2EApp/), contributing to research being carried out in the Mission Atlantic (https://missionatlantic.eu) research programme.

The successful applicants will have obtained at least an honours degree and preferably a Masters in a quantitative field of marine environmental science. They will need to demonstrate an up-to-date knowledge of research on marine fisheries and/or climate change, and their effects on food webs and the marine environment. They will also show an aptitude for writing research reports, and have experience of coding in R.

For any informal enquiries, please contact Chancellors fellow, Jack Laverick (jack.laverick@strath.ac.uk)

please click here for further details.pdf


University of Strathclyde

Finland

Samuel Kaski’s research group Probabilistic Machine Learning is searching for postdocs to work on AI fundamentals in exciting projects. The work includes collaboration with the Finnish Center for Artificial Intelligence (FCAI), the Centre for AI Fundamentals at the University of Manchester, the Alan Turing Institute, ELLIS and the new ELLIS Institute Finland, and researchers from other fields.

Prof Kaski is Professor of Computer Science in Aalto University and Professor of AI in the University of Manchester. He is Director of Finnish Center for Artificial Intelligence and ELLIS Unit Helsinki. His research group develops machine learning principles and methods focusing on a few key topics (see “Machine learning foundations” below), often working with researchers of other fields in new exciting applications (see the other topics below).

Topics

Machine learning foundations

Keywords: probabilistic modelling, Bayesian inference, simulation-based / likelihood-free inference, multi-agent RL and collaborative AI, sequential decision making and experimental design, privacy-preserving learning, Bayesian deep learning, generative models

We are looking for a new postdoc in the team which develops probabilistic modelling and Bayesian inference methods. The team has several exciting new machine learning formulations we work on, and opportunities for applying the methods with top-notch collaborators. The core is always development of new methods, and with this call we are looking for talented researchers with background in machine learning, stats or CS (or other directly relevant topics) who are keen on developing the new methods. In the cover letter, let us know what you are interested in - if we are already working on it, all the better, but we are willing to listen to new ideas too.

Machine learning for synthetic biology and biodesign

Keywords: AI-based design, human-in-the-loop machine learning, collaborative AI, molecular modeling, graph neural networks, deep learning algorithms, generative models

We are searching for early career scientists to join our research team working towards next-generation machine learning methods for synthetic biology. The positions are available in two large multi-year projects (BIODESIGN and BIOFOUNDRY) focused on establishing virtual laboratories for protein engineering and biomanufacturing, implemented in collaboration between FCAI and VTT Technical Research Centre of Finland, and NSF Global Center on biofoundries. The aim of the projects is to design novel AI-based tools for bioengineering. These tools will combine cutting edge machine learning techniques, such as graph neural networks, deep generative models, Bayesian optimization, and human-in-the-loop learning with the synthetic biology expertise of VTT. The virtual laboratories are envisioned to have a wide range of applications in industry (e.g., new biochemicals, biomaterials and drugs), and to help the transition to a carbon-neutral society.

Applicants should have a strong academic record in computer science, mathematics, or statistics. Solid research experience in one or more of the following fields is beneficial: AI-based design, Deep learning algorithms, Generative models, Human-in-the-loop machine learning, Collaborative AI, Molecular modeling, Reinforcement learning, Structured prediction.

The successful applicants will join a world-class research team with top AI researchers from FCAI and synthetic biology experts from VTT.

Real-time AI-assistance with computationally rational user models

Keywords: collaborative AI, human-in-the-loop ML/RL, reinforcement learning, user modelling

Despite recent advances in AI and machine learning, there are few AI solutions that can be applied when we cannot precisely specify the objective or do not have suitable data to learn from. This is particularly salient and challenging in ad hoc assistance for human users in complex tasks such as scientific discovery. 

This project aims to address this issue by learning these objectives, and to assist, directly from interaction with the users. To do so, we develop reinforcement learning techniques for AI-assistants and computationally rational user models that take into account factors such as cognitive biases to reason about human decision-making. We push state-of-the-art in AI that, through inference over - and planning with - such user models, is able to tackle problems that are otherwise out of reach of mainstream AI solutions. 

Supported by a High-performance computing grant from the Research Council of Finland, we are looking to strengthen this team with postdocs with a strong academic record in computer science, mathematics, or statistics. Solid research experience in one or more of the fields listed under this topic is beneficial.

Team: this project will be carried out with a top expert on computational rationality, Prof. Andrew Howes of University of Exeter,  and experts in application domains.

Next generation distribution shifts

Keywords: distribution shift, out-of-distribution generalization, robust deployment, deep learning, experimental design

Robust algorithms for machine learning models are vital as the deployed scenario can differ from the training scenario in unexpected ways. Placing assumptions on the kind of distribution shift we expect, such as covariate or label shift, and accounting for it during training is common practice. However, these assumptions are often too restrictive for real-world settings, as the shifts encountered are typically more complex. Moreover, it is difficult to know a priori which shifts we need to account for. This project focuses on developing novel machine learning methods  that demonstrate robust performance by adapting to unforeseen shifts and diverse datasets during deployment.

We are looking for applicants with a strong academic record in computer science, mathematics, or statistics. Solid research experience in one or more of the following fields is beneficial: distribution shift, out-of-distribution generalization, out-of-domain generalization, sequential experimental design.

Your experience and ambitions

We expect the candidates to hold or be close to getting a relevant doctoral degree and have a solid background in the mathematics/statistics/computer science needed in machine learning.

Previous experience in the application fields is an advantage. Capability of both independent work and teamwork, and excellent written and spoken English are necessary.

What we offer

We provide

RESEARCH ENVIRONMENT

You will work in Professor Samuel Kaski’s research group (Probabilistic Machine Learning Group). We design collaborations as we go, according to what the research needs. Collaborators include but are not restricted to the other groups in the Finnish Center for Artificial Intelligence (FCAI), other sites of the European Laboratory for Learning and Intelligent Systems (ELLIS) and our new ELLIS Institute Finland, Centre for AI Fundamentals of the University of Manchester, the Turing Institute, and a number of excellent researchers in other fields in our applications. 

JOB DETAILS

Postdoc positions are typically made for up to three years. Starting dates are flexible. All positions are negotiated on an individual basis. We are strongly committed to offering everyone an inclusive and non-discriminating working environment. We warmly welcome qualified candidates from all backgrounds to apply and particularly encourage applications from women and other groups underrepresented in the field.

All our positions are fully funded and the salary is based on the Finnish universities’ pay scale. The starting salary depends on the level of the position and the previous experience and is typically increased as the experience grows. All employees have access to the occupational health care services and are covered by the Finnish national health insurance system.

Ready to apply?

Submit your application through our recruitment system Workday by the link below. The deadline for applications is  February 2 2025 at 23:59 Finnish time, 2024.

Required attachments


	Cover letter (1–2 pages). 
	CV
	List of publications (please do not attach full copies of publications)
	A transcript of doctoral study
	The degree certificate of your latest degree. If you don’t yet have a PhD degree, a plan of completion must be submitted.
	Contact details of two senior academics who can provide references. We will contact your referees if we need recommendation letters.


All materials should be submitted in English in a PDF format. Note: You can upload max. five files to the recruitment system, each max. 5MB.

Please note: Aalto University’s employees should apply for the position via our internal system Workday -> find jobs (not external aalto.fi webpage on open positions) by using their existing Workday user account.

Contacts: Coordinator Fang Wang (fang.wang@aalto.fi)

More Information

We are part of Finnish Centre for Artificial Intelligence FCAI and ELLIS Unit Helsinki. More information on their pages, and the frequently asked questions on this page.  

Aalto University (53rd in the Times Higher Education THE ranking list of most international universities in the world) is a community of bold thinkers where science and art meet technology and business. We are committed to identifying and solving grand societal challenges and building an innovative future. Aalto has six schools with nearly 12 000 students and a staff of more than 4000, of which 400 are professors. Our main campus is located in Espoo, Finland. Diversity is part of who we are, and we actively work to ensure our community’s diversity and inclusiveness. This is why we warmly encourage qualified candidates from all backgrounds to join our community.

The Department of Computer Science is an internationally-oriented community and home to world-class research in modern computer science, combining research on foundations and innovative applications. With over 40 professors and more than 450 employees from 50 countries, it is the largest department at Aalto University and the largest computer science unit in Finland. Computer science research at Aalto University ranks high in several prominent surveys (47th worldwide and 9th in Europe in Shanghai subject ranking 2019; and 56th worldwide in Times Higher Education subject ranking 2020).

About Finland

Finland is a great place for living with or without family – it is a safe, politically stable and well-organized Nordic society. Finland is consistently ranked high in quality of life and was just listed again as the happiest country in the world: https://worldhappiness.report/news/its-a-three-peat-finland-keeps-top-spot-as-happiest-country-in-world/. For more information about living in Finland: https://www.aalto.fi/services/about-finland

More info:

twitter.com/fcai_fi
linkedin.com/company/fcai
youtube.com/channel/UC7nUhposDgxzDOKns_H5J0w
Newsletter: http://eepurl.com/gVPBpf

Aalto.fi 

twitter.com/aaltouniversity 
facebook.com/aaltouniversity
instagram.com/aaltouniversity

More about Aalto University:

Aalto.fi
youtube.com/user/aaltouniversity
linkedin.com/school/aalto-university/
www.facebook.com/aaltouniversity
instagram.com/aaltouniversity
twitter.com/aaltouniversity


Aalto University

Australia, Darlington


	Full time continuing at Matilda Centre at Usyd Camperdown campus
	Opportunity for a passionate, motivated, and innovative senior leader to join the Matilda Centre for Research in Mental Health and Substance Use
	Base Salary $150,628 + 17% superannuation


About the opportunity

The Matilda Centre is seeking a driven senior leader to join the Centre Executive as the Centre Operations Manager. The Operations Manager leads the Centre professional services team providing exceptional operational support services to academic and professional researchers, and plays a key role as a member of the Centre Executive, driving the strategic development of the Matilda Centre and its integration with University and Faculty services, activities, policies and governance.

Reporting to the Head, FMH Centres and Affiliated Institutes, in the Faculty of Medicine and Health, the Matilda Centre Operations manager is a key contributor to the strategic and operational development of FMH Centres, and plays an important role in driving change that has significant impacts on the daily operational and research tasks across FMH Centres. Responsible for Matilda Centre Operations, the Centre Operations Manager works closely with the Matilda Centre Director to deliver the Centre strategy.

Your key responsibilities will be to:


	provide leadership support and strategic advice on the development of the Centre, with consideration of the operational implications of strategic and other initiatives as a key member of the Centre Executive
	ensure the provision of the highest quality research support services across a broad suite of needs, including office management, research administrative support, budget and contract support, and engaging and connecting Centre researchers with University and Faculty processes and support teams
	ensure the operations of the Matilda Centre are undertaken to the highest standards, including operations to University and external policies and governance
	oversight and control of the Centre budget, providing timely and accurate information to the Executive to support budget planning and expenditure decisions
	undertake centre reporting and other activities required by the University Centres policy and Faculty requirements for Centre reporting
	lead and inspire staff, focusing on performance management, professional development, and career growth
	promote workplace safety, ensure legislative compliance, and mitigate risks effectively
	support projects and programs aimed at improving FMH Centre operations, and ensure Centre compliance with Faculty processes and effective engagement with Faculty support teams.


About you


	hold a tertiary qualification or equivalent combination of training and experience
	advanced expertise in strategy formulation, operational management, and decision-making
	proven experience in people management, including staff performance and development.
	demonstrated ability to interpret and apply legislation and policy in an academic context.
	strong capabilities in stakeholder engagement, negotiation, and collaboration.
	advanced skills in planning, project management, and analytical problem-solving
	proven commitment to diversity and inclusive work practices
	extensive broad administrative skills including complex budget and financial management, contracts and agreements, business data collection and reporting, research systems and processes
	extensive broad administrative skills including complex budget and financial management, contracts and agreements, business data collection and reporting, research systems and processes
	Strategic Thinking: Navigate complex landscapes to achieve university objectives
	Leadership: Inspire teams to deliver excellence while fostering a collaborative environment.
	Adaptability: Maintain composure and professionalism in dynamic circumstances
	Digital Proficiency: Leverage technology for operational efficiency
	Research Understanding: Navigate the unique legislative and funding environment of research.


Note:  University Shutdown: The University is closed for its annual seasonal break from Saturday 21 December 2024, returning to regular business operations on Tuesday 7 January 2025. During this period, the entire Recruitment Operations team will not be available to respond to enquiries.

Sponsorship / work rights for Australia

Please note: Visa sponsorship is not available for this position. This role requires valid work rights for Australia.

Pre-employment checks

Your employment is conditional upon the completion of all role required pre-employment or background checks in terms satisfactory to the University. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment.

As this position is located on an NSW Health site, it is a regulatory requirement to complete compulsory employment checks prior to starting in this position. For more information and instructions, please visit:NSW Health employment requirements

This position is designated as involving child-related work. To undertake or remain in this position, you are required to apply for and obtain a Working with Children Check clearance in accordance with the Child Protection (Working with Children) Act 2012.

EEO statement

At the University of Sydney, our shared values are trust, accountability and excellence and we strive to be a place where everyone can thrive. We are committed to creating a University community that thrives through diversity and reflects the wider community that we serve. We deliver on this through our commitment to diversity and inclusion, evidenced by our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTIQ+. We welcome applications from candidates from all backgrounds.

We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Gold employer. Find out more about our work on diversity and inclusion.

How to apply

Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page.

For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply.

For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Deepna Chand, Recruitment Operations by email to Deepna.Chand@sydney.edu.au 

Copyright The University of Sydney

The University reserves the right not to proceed with any appointment.

Click to view the Position Description for this role.

Applications Close

Sunday 19 January 2025 11:59 PM


The University of Sydney

United Arab Emirates, Abu Dhabi

Postdoctoral Associate/Research Scientist in the Division of Engineering (Civil and Urban Engineering) - Dr. Mohamed Moustafa 

Description

The Future-Generation of Resilient and Infrastructure Design Technology Hub (Future-GRID TecH) in the Division of Engineering at New York University Abu Dhabi, seeks to recruit one or more motivated post-doctoral associates (or research scientist for experienced candidates with 5 years of post-PhD experience). The candidates will work under the supervision of Future-GRID TecH director Dr. Mohamed Moustafa to carry out cutting-edge research in the broad area of future structures and resilient infrastructure systems with interest in applications of new and emerging technologies. Particular areas of interest include:


	advanced construction and reinforcement materials (UHPC, ECC, SMA)
	UHPC mix development, material characterization, modeling, and structural design
	structural 3D printing (metals, concrete, and composites)
	computational mechanics and structural topology optimization
	vision-based structural health monitoring
	autonomous and drone-based infrastructure inspection and vibration monitoring


Successful candidates must hold a PhD degree in Civil, Structural, Mechanical, or Material Engineering. Other related field such as Computer Science, Nuclear Engineering, and Material Science are also welcomed. Required qualifications include: strong communication and presentation skills; a track record in writing and publishing peer-reviewed journal publications; and previous or relevant experience in mentoring or supervising undergraduate student research or junior graduate students.

A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning, artificial intelligence, computer vision, robotics, UAVs, computational fluid dynamics, etc. is a plus. Other preferred qualifications include: expertise in programming and coding (preferably using Python and C ) and GUI development; expertise in computational mechanics and finite element simulation and modeling; expertise in laboratory and multi-scale experimental testing at the material, component, and structural levels.  

The candidates will work in a multidisciplinary environment consisting of PhD-level scientists and undergraduate students, conduct high-quality “innovative and independent” experimental, analytical, and/or computational research, publish research work and results in scientific peer-reviewed journals and conferences, mentor undergraduate students, and participate in writing research grant proposals.

To be considered, all applicants must submit the following documents in PDF format via Interfolio:


	cover letter
	curriculum vitae with full publication list
	statement of research interests and plan
	three sample (recent and/or most relevant) journal publications
	contact details of two references


The terms of employment include a highly competitive salary, medical insurance, housing allowance, annual home-leave travel, and educational subsidies for children (if applicable). Applications will be accepted immediately and candidates will be considered until the positions are filled.

If you have any questions or require more information, please email: mohamed.moustafa@nyu.edu

About NYUAD:

NYU Abu Dhabi is a degree-granting research university with a fully integrated liberal arts and science undergraduate program in the Arts, Sciences, Social Sciences, Humanities, and Engineering. NYU Abu Dhabi, NYU New York, and NYU Shanghai, form the backbone of NYU’s global network university, an interconnected network of portal campuses and academic centers across six continents that enable seamless international mobility of students and faculty in their pursuit of academic and scholarly activity. This global university represents a transformative shift in higher education, one in which the intellectual and creative endeavors of academia are shaped and examined through an international and multicultural perspective. As a major intellectual hub at the crossroads of the Arab world, NYUAD serves as a center for scholarly thought, advanced research, knowledge creation, and sharing, through its academic, research, and creative activities.

EOE/AA/Minorities/Females/Vet/Disabled/Sexual Orientation/Gender Identity Employer

UAE Nationals are encouraged to apply

Equal Employment Opportunity Statement

For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr

NYU is an equal opportunity employer committed to equity, diversity, and social inclusion.


Trakia University

About

Rankings

World University Rankings 20251501+

Impact Rankings

Impact Rankings 20241001-1500^th

No Poverty 20241001+

Zero Hunger 2024401-600^th

Good Health and Wellbeing 2024601-800^th

Quality Education 2024201-300^th

Affordable and Clean Energy 2024601-800^th

Industry, Innovation and Infrastructure 2024801-1000^th

Peace, Justice and Strong Institutions 2024801-1000^th

Partnership for the Goals 20241001-1500^th

Discover similar universities

Key Student Statistics

Company

Legal

Trakia University

About

Rankings

Impact Rankings

Impact Rankings 20241001-1500th

No Poverty 20241001+

Zero Hunger 2024401-600th

Good Health and Wellbeing 2024601-800th

Quality Education 2024201-300th

Affordable and Clean Energy 2024601-800th

Industry, Innovation and Infrastructure 2024801-1000th

Peace, Justice and Strong Institutions 2024801-1000th

Partnership for the Goals 20241001-1500th

Discover similar universities

Key Student Statistics

Impact Rankings 20241001-1500^th

Zero Hunger 2024401-600^th

Good Health and Wellbeing 2024601-800^th

Quality Education 2024201-300^th

Affordable and Clean Energy 2024601-800^th

Industry, Innovation and Infrastructure 2024801-1000^th

Peace, Justice and Strong Institutions 2024801-1000^th

Partnership for the Goals 20241001-1500^th