North University of China

Description The Center for Brain and Health (CBH) (https://brainandhealth.org/) at New York University Abu Dhabi (NYUAD) is seeking a Research Scientist to explore scientific questions related to an in-progress normative brain database. The Research Scientist will be a key member of a multidisciplinary team responsible for collection, c, MEG, EEG, and eye tracking. The tentpole of the CBH is a normative brain database - the first of its kind in the region - that includes structural, functional, and diffusion MRI, behavioral and health measures, genetic information, and lifestyle questionnaires Candidates must hold a Ph.D. in Neuroscience, Psychology, MR Physics, Data Science, Computer Science, or a related field. Postdoctoral experience or equivalent is preferred. This position requires extensive experience with multimodal MRI, including functional and structural MRI and tractography. Experience with big data analysis techniques is essential. Experience working with other large brain databases is preferred. The ideal candidate will possess strong computational skills and a strong publication record. Terms of employment include competitive salary and benefits. Applications will be accepted immediately. To be considered, applicants need to submit a cover letter, curriculum vitae with full publication list, transcript, statement of research interests, three representative publications, and three letters of reference, all in PDF format. For instructions and information on how to apply, please visit our website at http://nyuad.nyu.edu/en/about/careers/faculty-positions.html. If you have any questions, please email rokers@nyu.edu or kartik.sreenivasan@nyu.edu The anticipated appointment starting date is May 1, 2026, with funding guaranteed for a term of 18 months and opportunity for renewal of the position for additional years following performance evaluation. The terms of employment include highly competitive salary, housing allowance, and other benefits. 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.

Teaching ProfessorGeorgetown University: Main Campus: McDonough School of Business: Operations and Information ManagementLocation: Main CampusOpen Date: Dec 04, 2025Deadline: DescriptionThe McDonough School of Business (MSB) at Georgetown University invites applications for a full-time, 12-month Non-Tenure Line (NTL) Teaching Professor in the Operations and Analytics (OPAN) area. The appointment is expected to begin at the start of the Fall 2026 semester.This position covers 15-credits of teaching courses with emphasis on business analytics, statistics, management science, and data science in multiple programs across the MSB including the undergraduate, the Masters of Business Administration, the Master of Science in Business Analytics (Full-time and Online), and other specialized master's programs.In addition to teaching, the successful candidate is expected to collaborate with faculty to make continuous improvements to the curriculum and courses, and to advise students and engage with student leadership. Candidates are also expected to participate in some service or committee assignments similar to other full-time teaching faculty in the school.Candidates should hold a master's degree (a Ph.D. is preferred) from an analytics or business-related discipline. We are seeking dynamic candidates with demonstrated ability to successfully teach courses in the statistics, machine learning, and analytics space with relevant professional experience in the business analytics field who could also successfully advise student capstone projects in analytics. ABOUT THE MCDONOUGH SCHOOL OF BUSINESSGeorgetown University's McDonough School of Business offers unparalleled access to the world's business, policy, and thought leaders. The school, which attracts faculty and students from around the world, is committed to building global business knowledge and inspiring ethical leaders to serve the common good. Known for its emphasis at the intersection of business and global affairs and its values-based approach to business as part of Georgetown's rich Catholic, Jesuit tradition, the school also is focused on how business can be a force for change by addressing fields of the future, such as healthcare, sustainability, and AI and the future of work. The school's undergraduate and graduate degree programs provide solid grounding in all the core management disciplines, with an emphasis on the global, ethical, and political environment of business. The McDonough School of Business has an ongoing commitment to being a community in diversity as a fundamental aspect of the Georgetown community.APPLICATION PROCEDUREAll applications should be submitted electronically through Interfolio. Interested applicants should provide a cover letter, curriculum vitae, a complete set of teaching evaluations from recent years, and the names and contact information of three references.Consideration will begin January 15, 2026, but applications are welcome until the position is filled.The projected base salary range for this position is $145,000 - $170,000. Compensation is determined by a number of factors including, but not limited to, the candidate's individual qualifications, experience, education, skills, and certifications, as well as the University's business needs and external factors. QualificationsApplication InstructionsFor more information and to apply, visit https://apply.interfolio.com/178858GU is an Equal Opportunity Employer. All qualified applicants are encouraged to apply, and will receive consideration for employment without regard to age, citizenship, color, disability, family responsibilities, gender identity and expression, genetic information, marital status, matriculation, national origin, race, religion, personal appearance, political affiliation, sex, sexual orientation, veteran status, or any other characteristic protected by law.Copyright ©2025 Jobelephant.com Inc. All rights reserved.Posted by the FREE value-added recruitment advertising agency jeid-fa793868db871b47b0a041bc6c87c0a5

At the University of Vienna more than 10,000 personalities work together towards answering the big questions of the future. Around 7,500 of them do research and teaching, around 2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral 51 Faculty of Physics Startdate: 01.02.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 31.01.2029 Reference no.: 5031 Explore and teach at the University of Vienna, where more than 7,500 academics thrive on curiosity in continuous exploration and help us better understand our world. Does this sound like you? Then join our accomplished team! About the team: This is an opportunity to work towards a PhD in physics and to conduct world-leading research and teaching in molecular simulation and computational materials discovery. Fuel cells, photovoltaic devices, photocatalytic converters – they all are crucial elements in delivering decarbonization and sustainable energy production at a global scale within the coming decades. They all fundamentally involve energy transfer and chemical dynamics at interfaces where molecules, electrons, and light interact to deliver a certain function. The underlying mechanisms of ultrafast dynamics at surfaces triggered by light or electrons are not well understood, which, for example, limits our ability to design photocatalyst materials that deliver optimal light absorption, catalytic activity, and energy transport. Molecular simulation methods and quantum theoretical calculations in principle can address this but have hitherto struggled with tackling such challenging systems. With the emergence of machine learning methods in the physical sciences, things are rapidly changing. This project is part of a large initiative that aims to tackle this ambitious challenge by developing and applying new software tools that combine machine learning methodology, electronic structure theory, and molecular dynamics methodology to simulate ultrafast chemical dynamics at surfaces and in materials. Your personal sphere of influence: As a university assistant (praedoc), you will be part of the Computational Materials Discovery group of Professor Reinhard Maurer. This project will focus on the development of novel machine learning representations of electronic structure and quantum operators. These surrogate models will be combined with mixed quantum-classical dynamics simulation approaches to perform chemical dynamics simulations at an unprecedented scale. You will contribute to the development of broadly applicable electronic structure methods, new software, and machine learning methods with the specific goal to enable high throughput screening of optimal photocatalyst materials and to reveal important mechanistic insights into ultrafast dynamics and measurable spectroscopic properties. This will be done in close collaboration with a broad network of international collaborators. The employment duration is 3 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 3 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration.With appropriate work progress, an extension to a total maximum of 4 years is possible. Your future tasks: You will actively participate in research, teaching & administration. This means: You are involved in a curiosity-driven research project in the field of machine learning in computational materials science. You will present your research plan to the faculty and complete a dissertation agreement within 12-18 months. This will be reviewed and adapted on an annual basis. You will work on your dissertation and towards its completion in time. We expect a large degree of independence paired with a high level of social awareness as the goal will only be achieved in a team. You will contribute to teaching (exercise classes) within the provisions of the collective bargaining agreement. You will fill some administrative tasks, contributing to the success and self-organization of the group for research, teaching and administration. You will continuously stay informed about the state of the art in your field. You will contribute to outreach by publications, conference presentations and public activities. Candidate profile: You have completed your Master's degree or Diploma in physics. You have experience in academic writing. You have an interest and background in condensed matter theory and electronic structure theory. You have an excellent command of written and spoken English. You should have experience with programming (e.g. Python, Julia), simulation methods (e.g. molecular dynamics) and modern machine learning methods. What we offer: In the Maurer group, we aim to develop computational simulation methodology to study quantum phenomena at surfaces with applications ranging from photocatalysis to nanotechnology and electrochemistry. Our goal is to combine electronic structure theory, molecular and quantum dynamics methodology, and machine learning methods to achieve an accurate yet computationally feasible description of complex phenomena in materials and at solid/gas and solid/liquid interfaces. You will join a large, international and interdisciplinary research group that provides a collaborative and supportive environment. Our team is member of the Vienna Doctoral School in Physics and the faculty research group Computational Materials Physics. PhD students in the group acquire important transferable skills such as software development and project management. You will present your research at international and national conferences. Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment. Potential for development: Success in life depends on what you make of it, but if you are ambitious and self-driven, there are plenty of opportunities to connect you to all relevant top research groups in the world. Good public transport connection:  Your new workplace is easily accessible by public transport. Internal further training & Coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your skills in over 600 courses to choose from – free of charge. Fair salary: The basic salary of EUR 3.776,10 (on a full-time basis, 14x p.a.) increases if we can credit professional experience. Equal opportunities for everyone: We strive to create a fair and equitable work environment, where diversity is an asset and individuals can flourish. It is that easy to apply: Your scientific curriculum vitae. A summary of your previous academic and research achievements. Tell us about your moments of professional pride. A short statement on your research interests for the future (motivation letter). Tell us what you dream about, scientifically. Your Bachelor’s and Master's degree: an excellent academic degree is a good entrance statement for this position. Note, that while a Master’s degree is the usual legal prerequisite for a PhD position at the University of Vienna, we can consider Bachelors (preferentially with Honors) in exceptional cases, too. If you have any content questions, please contact: Reinhard Maurer reinhard.maurer@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: 01/30/2026 Prae Doc