Sudan University of Science and Technology

The Health and Social Sciences Cluster at SIT has been at the forefront of allied health education and research, offering a suite of allied health programmes and two nursing programmes. As a young university, we foster an academic environment that seamlessly integrates teaching, applied research and clinical practice. We offer competitive remuneration, generous employment benefits, access to funding to undertake clinical research, and opportunities to inspire and nurture the next generation of skilled allied health and nursing professionals. About the Positions We currently have positions available from Assistant Professor to Full Professor, for the following disciplines: Diagnostic Radiography Dietetics Nursing Occupational Therapy Physiotherapy Speech and Language Therapy Applicants should meet all the criteria below: (a) an earned PhD in the respective healthcare discipline from a reputable university; (b) excellent research track record; (c) deep clinical experience in the respective healthcare discipline. We will prioritise collegial and team-spirited candidates with an earned PhD in a related discipline from a reputable university, plus relevant work experience or experience of industry-linked applied research projects. Applications will be accepted until the positions are filled. All applications must be submitted electronically via the "Apply Now" button below. 

Description The Modern Compilers Lab in the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon are building new specialized programming frameworks. This is because these companies need to allow their users to write simple, high-level code and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures without changing the code. Our research team at NYUAD (New York University Abu Dhabi) is developing a new programming framework called Tiramisu [1]. Unlike existing frameworks, Tiramisu can perform advanced code optimizations that are hard to apply otherwise. Because of this, Tiramisu can generate fast code that outperforms highly optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel), enhancing data locality by fusion, and blocking (i.e. accessing arrays in a way that improves temporal and spatial data locality). A large number of optimizations exist and choosing which optimization should be used and which should not is important for performance. In some situations, some optimizations are harmful to performance while they are beneficial in other situations. Currently, there is no way to help users choose which optimizations should be used. Expert programmers usually spend a lot of time trying different optimizations manually to find the best set of optimizations. The goal of this project is to add support for automatic code optimization in Tiramisu. In particular, we want to use machine learning/deep learning to achieve this. Currently, a basic automatic optimization module that relies on machine learning has been developed and we want to take that module to the next level. The final product of this project would be a compiler pass that allows Tiramisu to automatically choose which optimization should be used for a given unoptimized program. We want to produce a high-quality technique that can be used by the users of Tiramisu and especially by our partner companies and research labs. Candidates must hold a bachelor’s degree or equivalent in Computer Science, though a master’s degree is preferred. The ideal candidate will have Internship or experience in the areas of compilers and artificial intelligence. For consideration, applicants need to submit a cover letter, curriculum vitae, transcript, statement of research interests and two letters of reference, all in PDF format. If you have any questions, please email Prof. Riyadh Baghdadi at baghdadi@nyu.edu or mrasras@nyu.edu. The terms of employment are very competitive and include housing and educational subsidies for children. Applications will be accepted immediately and candidates will be considered until the position is filled. About NYU Abu Dhabi https://nyuad.nyu.edu/en/ NYU Abu Dhabi is the first comprehensive liberal arts and research campus in the Middle East to be operated abroad by a major American research university. Times Higher Education ranks NYU among the top 30 universities in the world, making NYU Abu Dhabi the highest-ranked university in the UAE and MENA region. NYU Abu Dhabi has integrated a highly selective undergraduate curriculum across the disciplines with a world center for advanced research and scholarship. The university enables its students in the sciences, engineering, social sciences, humanities, and arts to succeed in an increasingly interdependent world and advance cooperation and progress on humanity’s shared challenges. NYU Abu Dhabi’s high-achieving students have come from over 120 countries and speak over 100 languages. Together, NYU's campuses in New York, Abu Dhabi, and Shanghai form the backbone of a unique global university, giving faculty and students opportunities to experience varied learning environments and immersion in other cultures at one or more of the numerous study-abroad sites NYU maintains on six continents. NYUAD is committed to upholding a culture of non-discrimination, anti-harassment, dignity, and mutual respect; providing equal access and opportunity; and fostering academic excellence in learning, research, and teaching. UAE Nationals are encouraged to apply. References [1] http://tiramisu-compiler.org/

At the University of Vienna, over 10,000 people work together on the big questions of the future. Approximately 7,500 of them are academic staff members. These are individuals who, with their curiosity and their continuous pursuit of excellence, engage in international cutting-edge research and teaching. With us, you will also find space to unfold your potential. We are looking for a/an  University assistant predoctoral 34 Faculty of Law Startdate: 01.07.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.06.2029 Reference no.: 5714 The Institute for Labour and Social Law invites applications for four pre-doctoral assistant positions (employment group B1, in accordance with the collective agreement) to support the research team of Prof. Dr. Erika Kovács, who will assume her position at the Institute on 1 February 2026. Her focus is on European labour law. Your personal sphere of influence: As a predoctoral university assistant, you will conduct your own independent research, be responsible for teaching and examination duties, and provide support in research, organizational, and administrative tasks. Your future tasks: You will be actively involved in research, teaching and administration, which means: Collaboration in research and teaching in the field of labour and social security law. We expect you to finalise your dissertation agreement within 12-18 months. You will work on your dissertation and its finalisation as well as other academic work. You will teach courses independently in accordance with the provisions of the collective bargaining agreement. You will be responsible for administrative tasks in research and teaching. This is part of your personality: Completed Master’s degree or Diploma in Law Strong expertise in labour and social law, with a particular interest in European labour and social law Above-average academic achievements Excellent written and spoken English skills Proficiency in IT applications, including MS Office, Adobe Acrobat, and relevant databases Ability to work effectively in a team. The employment relationship of the university assistant is initially limited to 1.5 years and will be automatically extended to a total of 3 years unless the employer issues a statement of non-renewal within the first 12 months. An extension to a total of 4 years is possible subject to probation and corresponding work progress. The position should ideally be filled as soon as possible (preferably by 1 February 2026). Candidates with one or more of the following will be particularly well-suited for the position: Experience in preparing applications for research projects Experience in project management or coordinating research projects Prior experience in academic research or publication Moot court experience Academic or professional experience abroad, such as a semester abroad Proficiency in additional language What we offer: Work-life balance: Excellent compatibility of professional and private life Inspiring working atmosphere: You will be part of an international team with excellent research infrastructure in a relaxed working environment. Good public transport connections: Your new workplace is easily accessible by public transport. Fair salary: The basic salary of EUR 3.714,80 (based on full-time employment) increases if we can take your professional experience into account. It is that easy to apply: Academic CV Cover letter including research interests Notification of completed master's/diploma degree (degree certificate) List of publications (if available) Via our job portal / Apply now button Via our job portal / Apply now - button If you have any questions, please contact: Erika Kovacs erika.kovacs@univie.ac.at We look forward to new personalities in our team! The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We lay special emphasis on increasing the number of women in senior and in academic positions among the academic and general university staff and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates. University of Vienna. Space for personalities. Since 1365. Data protection ​Application deadline: 06/24/2026 Prae Doc