University of Basrah

Employment Type: Full - time (35 hours a week) Duration: 2 Year Fixed Term Remuneration: $113,911 - $137,092 base (+17% super, annual leave loading) Location: Randwick, Sydney (Minimum 3 days in the office required). About the role This position will undertake research using the Kids and Sibs study, a longitudinal investigation examining predictors of bipolar disorder development in a high-risk population with up to 15 years of follow-up. The study includes rich phenotypic data, as well as neuroimaging and blood biomarkers (including genetic data) on up to 440 individuals, with varying lengths of follow up (PI Mitchell). The data are aligned with an international dataset (across four US Universities) ensuring opportunities for robust replication. We also encourage applicants with broad interests in neuroscience and epidemiology relating skills, as additional research opportunities are available using linked data research, and intervention development/evaluation (PI Ratheesh). Applicants with prior research expertise relating to bipolar disorder or depression are especially encouraged. The position is part funded by the Centre for Research Excellence in Bipolar Disorder (https://www.corebd.com.au/). Key skills and experience required: Level A A PhD in a related discipline, and/or relevant work experience. An understanding of youth mental health, mood disorders, prevention and prediction that supports such data analyses. Proven commitment to proactively keeping up to date with discipline knowledge and developments. Demonstrated ability to undertake high quality academic research and conduct independent research with limited supervision. Conceptualisation and completion of data analyses with skills related to epidemiology or neuroscience. Demonstrated track record of publications and conference presentations relative to opportunity Demonstrated ability to work in a team, collaborate across disciplines and build effective relationships. Evidence of highly developed interpersonal and organisational skills. Demonstrated ability to communicate and interact with a diverse range of stakeholders and students. Excellent time management with a proven ability to deal with multiple tasks, establish priorities, and meet deadlines. Level B (in addition to the above) Demonstrated track record in research with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research excellence as well as the capacity for research leadership. A track record of significant involvement with the profession and/or industry. High level communication skills and ability to network effectively and interact with a diverse range of students and staff. Full details can be found in the position description. UNSW Benefits and Culture: People are at the core of everything we do. We recognise it is the contributions of our staff who make UNSW one of the best universities in Australia and the world. Our benefits include:  Flexible Working arrangements (work from home, flexible hours) Additional 3 days leave during Christmas holidays Career development opportunities Up to 50% discount on UNSW courses Flexible 17% Superannuation contributions, additional leave-loading payments and salary sacrifice. Discounts and entitlements (retail, education, fitness passport) How to apply: Please click on THIS LINK to apply. Applications should not be sent to the contact listed below. Please provide a resume and a separate cover letter addressing the key skills and experience for the role listed in the Position Description. Pre-Employment Checks Aligned with UNSW’s focus on cultivating a workplace defined by safety, ethical conduct, and strong integrity preferred candidates will be required to participate in a combination of pre-employment checks relevant to the role they have applied for. These pre-employment checks may include a combination of some of the following checks: Confirmation of Aboriginality documentation National and International Criminal history checks Entitlement to work and ID checks Working With Children Checks Completion of a Gender-Based Violence Prevention Declaration Verification of relevant qualifications Verification of relevant professional membership Employment history and reference checks Financial responsibility assessments/checks Medical Checks and Assessments Compliance with the necessary combination of these checks is a condition of employment at UNSW. Role enquiries: Merita O'Connell, Talent Acquisition Partner E: merita.oconnell@unsw.edu.au Applications close: Thursday 2nd July, before 11.30pm Sydney time. UNSW is committed to equity diversity and inclusion. Applications from women, people of culturally and linguistically diverse backgrounds, those living with disabilities, members of the LGBTIQ+ community; and people of Aboriginal and Torres Strait Islander descent, are encouraged. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.

Department of Computer Science of Faculty of Science invites applications for a DOCTORAL RESEARCHER IN MACHINE-LEARNING, STATISTICS AND DATA-CENTRIC ENGINEERING starting from September 2026, or as agreed. The Doctoral Researcher will be offered a full-time contract for the maximum duration of 3 years (possibly extendable to 3.5-4 years). There will be a trial period of six months at the beginning of employment.  Position description The successful candidate will work within the research project “Advances in generalized Bayesian inference via differential-geometric methods” funded by the Research Council of Finland under the supervision of the Academy Research Fellow Marcelo Hartmann and Research Fellow Luu Hoang Phuc Hau (Nanyang Technological University). We have been developing computational algorithms and theory grounded in notions of information geometry and Riemannian geometry to enhance Bayesian statistical inference and machine-learning related methods. The successful deployment of statistical models and AI solutions relies heavily on the quality of underlying model assumptions and the learning algorithms they employ. The design of loss functions is therefore crucial in the process of model development to the specific tasks at hand. For instance, the Hyvärinen score matching principle has been widely applied in AI systems, particularly for tasks such as diffusion-based image generation. This project seeks to further develop and broaden the range of loss functions by incorporating concepts from differential geometry. Additionally, we leverage the theory of estimating functions to create optimal inference algorithms for the proposed loss functions based on its underlying Riemannian geometry, as well as for those previously introduced in the literature. These advancements hold significant potential for a wide range of applications, spanning scientific research and societal challenges at large. The primary research site is the Department of Computer Science at the University of Helsinki (UH), strong synergy also exists between researchers at the Department of Computer Science at Aalto University, supported by the flagship grant from the Research Council of Finland (RCF) for AI research, called the Finnish Center for Artificial Intelligence (FCAI). This project is further related to the European Laboratory for Learning and Intelligent Systems (ELLIS unit Helsinki and ELLIS Institute Finland). Both institutes aim to foster cutting-edge research and establish a globally recognized concentration of expertise in ML and Statistics. You will also have the chance to collaborate with researchers from University of Cambridge (UK), Technical University of Denmark, University of Warwick, Nanyang Technological University and Hamburg University of Technology. Please check our personal website (as hyperlinks in our names) for details and news. The Doctoral Researcher is expected to: advance the research project together with the project leader and conduct doctoral studies and research work leading to a completed PhD thesis within 4 years. Your work may also include teaching duties (at most 5% of annual working time). Requirements and eligibility criteria The doctoral researcher should have a Master's degree in Statistics, Mathematics or Computer Science (or a related field) with an emphasis on applied mathematics/statistics/machine-learning. Prior experience in the probabilistic machine-learning, neural-networks, statistical inference and data modelling is a bonus. Prior experience in some computer programming language is expected (Python, Julia, R, Matlab etc). Excellent communication skills in English, both verbal and written, are naturally expected. In addition, according to the system of the University of Helsinki, all doctoral researchers belong to a doctoral programme. The successful candidate should apply to Doctoral Programme in Science and obtain the study right within the trial period of six months of their employment contract. Please check the admission periods and eligibility criteria at https://www.helsinki.fi/en/admissions-and-education/apply-doctoral-programmes/how-apply-doctoral-programmes Salary and benefits The starting salary of the Doctoral Researcher will be ca. 2800 euros/month, depending on the appointees’ qualifications and experience. The salary will develop in accordance with the progress of studies. The University of Helsinki offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The University provides support for internationally recruited employees with their transition to work and life in Finland. Finland and the Helsinki region possess top expertise in sciences in terms of a vibrant talent pool, leading research, strong support services and functioning collaboration networks Finland is a member of EU, has high quality free schooling (also in English), generous family benefits and healthcare, and has been ranked as the happiest country in the world for eight consecutive years. For more information about working at the University of Helsinki and living in Finland, please see https://www.helsinki.fi/en/about-us/careers. A diverse and equitable study and work culture is important to us. That is why we do our best to promote an inclusive university community. We encourage all qualified applicants from diverse backgrounds to apply for our positions. Click this link to read about accessibility and inclusivity at our university How to apply Please submit your application, which includes the following documents in English: A motivation letter describing why you are interested in this position and how you are qualified (max. 1 page) A curriculum vitae including a list of publications (if any). One example of a written analytical text (e.g. Master’s thesis). If the text is not solo-authored, detail your contribution to producing the text. The names and contact information of two referees, who are willing to provide reference letters upon request (optional). External applicants, please submit your application through the University of Helsinki’s recruitment system via the Apply Now button. Internal applicants, applicants who have a helsinki.fi username and a valid employment/grant/visitor contract at the University of Helsinki are requested to submit their application via the Employee login button. We are eager to fill this position as soon as possible and therefore encourage early applications. However, the absolute deadline for submitting applications is July 15th, 2026 (at 23:59 UTC +2). More information? For questions project and position related questions, please contact  Academy Research Fellow (PI) Marcelo Hartmann, marcelo.hartmann@helsinki.fi For more information on the PI and publications, see https://www.helsinki.fi/en/researchgroups/multi-source-probabilistic-inference With technical questions related to the recruitment system, please contact recruitment@helsinki.fi. *** fThe Department of Computer Science is a leading unit in Finland in its area and responsible for the teaching and research in computer science at the University of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive international collaboration with companies and universities. Within teaching, the department’s professors and staff are in charge of the Bachelor’s, Master’s, and Doctoral Programmes in Computer Science, as well as the separate master's Programme in Data Science, in which other departments also participate. 

The Role and Department The Department's undergraduate curriculum is notable for its historical and cultural breadth, combining compulsory modules in Theory, Shakespeare and an independent Dissertation, with a range of period-based modules taught by lectures and tutorials, and research-led special topic semininars. There are thriving MA programmes in English Literary Studies and in Creative Writing, and a lively community of PhD students. Applications are invited for a Teaching Fellow in Early Modern Literature. This is a 1.0 FTE position for 12 months only. The successful applicant will: Teach undergraduate tutorials in Introduction to Drama (Level 1) and seminars on John Milton (Level 2). Potentially contribute to Renaissance Literature and/or Shakespeare. Deliver lectures as required in these areas. Supervise Level 3 undergraduate dissertations. Potentially supervise MA theses. Contribute to lively and stimulating small group teaching, in person. Undertake assessment and examination of UG and MA student work, in and beyond Early Modern Literature. Act as an Academic Advisor to a group of UG students. Participate in the meetings of the Department as appropriate. Pursue opportunities for personal development. The post-holder will report to the Head of Department. Career development opportunities will be offered. Teaching Fellowships offer the opportunity of valuable experience to those early in their academic careers and the University is keen to maximise the benefit to as many people as possible.The post of Teaching Fellow will involve a significant teaching load, which may extend into the summer period, and there may be related scholarship and the opportunity for administrative duties which relate to education and pedagogy. The post is for a fixed term only, and it is not anticipated that the post will be extended beyond this fixed term. Successful applicants will, ideally be in post by 1 September 2026 . The University provides a working and teaching environment that is inclusive and welcoming and where everyone is treated fairly with dignity and respect. Candidates will be expected to demonstrate these key principles as part of the assessment process.