Istanbul Technical University

Location: Doha,QA Department Name: Public Health Department Qatar University profile:http://www.qu.edu.qa/ Qatar University is the national institution of higher education in Qatar, comprising nine colleges and offering the largest selection of undergraduate and graduate programs in the country. Qatar University seeks the highest international accreditations of its academic programs, while ensuring they are aligned with the growing needs of the labor market and the aspirations of the society it serves. It currently boasts a population of over 20,000 students, and an alumni body of over 40,000. QU Health http://www.qu.edu.qa/health Qatar University launched the QU Health Cluster in January 2017 to provide closer alignment and integration between the health entities at QU. Together, the College of Medicine, the College of Health Sciences, and the College of Pharmacy create a dynamic environment that embraces experts in the education of health care professionals. Areas of collaboration at QU Health include research, graduate studies, clinical affairs, continuous professional development, inter-professional education, engagement and communication, as well as business operations. http://www.qu.edu.qa/chs/ In 2016, the College of Health Science (CHS) became the ninth college at Qatar University, building on a 30-year success story as a department. CHS is the national provider of high quality health sciences education and research in Qatar, offering undergraduate (BSc) programs in biomedical sciences, human nutrition, public health, and physiotherapy as well as graduate programs in biomedical science, genetic counseling and public health. CHS faculty members have excellent opportunities to secure intramural and extramural research funding. Qatar National Research Fund (QNRF) is major source of research funding, including a variety of student research funding programs. The position The College of Health Sciences is seeking to recruit a qualified candidate for a position in Public Health at the level of Teaching Assistant. The successful candidate will assist faculty members at the Department of Public Health in assessing and administering courses related (but not exclusive) to biostatistics and epidemiology. The position also involves delivering tutorial sessions and running student workgroups, in addition to student advisory role. Duties & Responsibilities Prepare and deliver practical/ lab/ tutorial sessions. Under the supervision of the course instructor, teach independently introductory and/or other professional and technical–based sessions. Assess and evaluate student assignments/ tests, quizzes, exams/ project and grade student performance under the direct supervision of course instructors. Provide academic assistance to students during office hours. Assist with senior students' graduation projects. Organize field trips and supervise internship and field studies. Serve on departmental or faculty committees dealing with general departmental and administrative concerns, as assigned by Head of Department. Contribute to academic advising and assist in Department/College events Support research activities in the department  Other responsibilities as assigned by the Head of Department Qualifications Master’s degree in biostatistics, or epidemiology, or a similar field. At least two-year experience in running tutorials in Biostatistics and Epidemiology to public health and/or medical students in an academic or clinical setting Familiarity with educational technologies in higher education Flexibility in dealing with various academic and administrative tasks Excellent written and oral communication skills Ability to communicate clearly with students on an individual basis or in small groups and to liaise with faculty members. Arabic language is preferable. Required Documents Academic: Current Curriculum Vitae. Cover letter. Teaching, research, and service philosophy. Three referees’ contact information (physical and email addresses as well their telephones contact). Copy of highest earned credential (transcript of highest degree if graduated from an institution where course work was completed. However, if no course work was completed, an copy of certificate letter from the registrar of your highest credential granting institution regarding your highest academic degree). Any additional documentation that you feel is relevant to your application. Benefits Academic: A three-year renewable contract. Salary is commensurate with experience. Tax-free salary.    Furnished accommodation in accordance with QU HR policies. Annual round trip air tickets for faculty member and dependents in accordance with QUHR policies. Educational allowance for candidate's children (eligible candidates only) in accordance with QU HR policies. Private health care and health insurance in accordance with QU HR policies. Annual leave in accordance with QU HR policies. End-of-contract indemnity. How To Apply                 Returning Applicant:  Please login in QU Recruitment Online website (https://careers.qu.edu.qa) to update/edit your saved profile. Use this profile to apply for this position. New Applicant:  You need to setup an account with QU Recruitment Online website (https://careers.qu.edu.qa) and complete your personal profile. Once your profile is complete you may use it to apply for an open Position. Job Category: Academic End Date of Advertisment: 15-Feb-2026

About Us The post will be based at St Thomas’ Hospital in central London in the School of Biomedical Engineering & Imaging Sciences at King’s College London: https://www.kcl.ac.uk/bmeis . There is an unmatched infrastructure within the School to support cutting-edge translational research, including one of the UK’s only 7 Tesla MRI systems located inside a hospital environment, state-of-the-art engineering and physics laboratories, high-performance computing, and industry collaboration through the London Institute for Healthcare Engineering. About The Role Severe epilepsy has a devastating impact on the lives of patients and their families. For many patients’ medication is ineffective and surgery is the only curative treatment. However, surgery requires confident knowledge of the location of the epilepsy lesion (abnormal tissue whose aberrant electrical activity causes seizures). We are pioneering the use of Ultra-high field 7T MRI and AI based lesion detection to allow more patients to benefit from life-changing surgery. You will join a project team of post-doctoral scientists, Imaging physicists, Neurologists, Clinical Neurophysiologists and Neuro-Radiologists at KCL and Cambridge Universities and their partner hospitals to achieve this aim. You will be responsible for optimising data acquisition and processing through novel methodological development in either image acquisition, reconstruction or post-processing (e.g. AI-based lesion identification) under the primary direction of Prof David Carmichael. You will also ensure the delivery of high-quality data to the clinical research team to meet the clinical research objectives. This is a full time post (100% FTE), and you will be offered fixed term contract until 10th November 2029. About You You will be a technically gifted researcher establishing a strong academic track record. You may have worked in MRI research previously or have strong computational / AI / machine learning skills used in other areas of research.  Essential criteria PhD qualified in relevant subject area Ability to work as part of a team to collect research data in patients Strong analytical and technical skills (e.g. in MRI physics, AI, image processing or reconstruction) Strong computational skills (e.g. coding in python, bash, matlab)  Demonstrated aptitude for research Problem solving ability Ability to work in a multidisciplinary team Ability to work without close supervision Desirable criteria Expertise in MRI physics and technology Experience in working together with physicians or scientists in the field of MR imaging or clinical research Experience of pulse sequence programming (particularly IDEA) or image reconstruction Experience of computational modelling and simulatxion Knowledge of statistical and/or machine learning methods e.g. for 3D imaging data for applications such as segmentation, registration or lesion detection. Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process. Further Information We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community.  We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible. To find out how our managers will review your application, please take a look at our ‘How we Recruit’ pages. Grade and Salary: £53,947 - £56,878 per annum inclusive of London Weighting Allowance Job ID: 133705 Close Date: 04-Jan-2026 Contact Person: David Carmichael Contact Details: david.carmichael@kcl.ac.uk

As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT.  Job Purpose The primary responsibility of this role is to deliver on an academic research project funded by BCA. The project is in collaboration with IHL and an industry partner. where you will be part of the research team to develop and demonstrate Building-to-Grid Integration through Intelligent Optimization and Predictive Control at SIT’s Punggol campus. Under this job title, you will be required to establish a test bed in SIT’s Punggol campus building, benchmarking of current building energy performances, deployment of new sensors & hardware, and quantitative evaluation of energy savings. You will be required to coordinate with multiple internal and external parties for the successful deployment of technology, test-bedding, and energy performance evaluation. Key Responsibilities Participate in and manage the research project with the Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met. Candidate will be required to establish test bed in SIT’s Punggol campus building, benchmarking of current building energy performances, deployment of new sensors, hardware, quantitative evaluation of energy savings, etc. Meeting the deliverables by deployment, demonstration, and experimental studies planned for under the scope of work of the projects within the timeframe to meet the deliverables. Coordination with project internal and external team members, vendors, contractors, safety officers, for successful deployment of technology and testing. Assists in the co-supervision of final year projects (FYP) or capstone projects students under the Project PI. Assists the PI in drafting project reports, conference proceedings, and journal articles based on the outcome of the projects. Prepares and shares a fortnightly report of results from the computations with the PI. Carry out Risk Assessment, and ensure compliance with Work, Safety, and Health Regulations. Work independently, as well as within a team, to ensure proper operation and maintenance of equipment. Job Requirements PhD degree in electrical/civil/mechanical engineering or other related fields Expert knowledge of building air-conditioning and mechanical ventilation, simulation, building automation and control, sensor network, thermal energy storage, indoor air quality, heat transfer, and building energy performance evaluation.  Experience of test bed setup development, testing & commissioning, and performance analysis. Knowledge of industrial protocols, sensors, and control hardware. Knowledge of building management systems, software integration, data collection, and analysis. Industry or research lab experience is required. Strong analytical and conceptual abilities. Ability to work in a team as well as independently. Able to work under pressure and meet deadlines. Key Competencies  Able to build and maintain strong working relationships with people within and external to the university. Able to work independently with strong data analytical skills, communication and interpersonal skills. Self-directed learner who believes in continuous learning and development Proficient in technical writing and presentation Possess strong analytical and critical thinking skills Show strong initiative and take ownership of work