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Xinjiang Medical University

Urumqi, China
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Post-Doctoral Associate in the Division of Engineering (Civil and Urban Engineering)

NEW YORK UNIVERSITY ABU DHABI

New York University Abu Dhabi Corporation

United Arab Emirates, Abu Dhabi

institution

New York University Abu Dhabi Corporation

United Arab Emirates, Abu Dhabi


Description The S.M.A.R.T. Construction Research Group at New York University Abu Dhabi (NYUAD), led by Prof. Borja García de Soto, is seeking to recruit a highly motivated Post-Doctoral Associate to conduct interdisciplinary research at the intersection of digital construction technologies and cybersecurity. The successful candidate will contribute to cutting-edge research focused on improving the security, resilience, and trustworthiness of the increasingly digitalized and connected built environment. Applicants with expertise in construction engineering and management, computer science, cybersecurity, artificial intelligence, robotics, digital twins, Building Information Modeling (BIM), or related disciplines are encouraged to apply. The S.M.A.R.T. Construction Research Group conducts world-leading research to advance the digital transformation of the architecture, engineering, construction, and operations (AECO) industry through automation, artificial intelligence, robotics, digital twins, BIM, and technology integration. A defining aspect of the group's research is the incorporation of cybersecurity considerations into emerging construction technologies to enable secure, resilient, and trustworthy digital ecosystems throughout the lifecycle of the built environment. The successful candidate will join a dynamic and interdisciplinary research environment and collaborate with faculty and researchers across NYU Abu Dhabi, the NYU Global Network, and leading international academic and industry partners. The successful candidate is expected to conduct high-quality, independent research leading to publications in leading peer-reviewed journals and conferences. Responsibilities include developing innovative research methodologies and decision-support frameworks, designing and implementing experimental studies, analyzing and interpreting research findings, contributing to proposal development, mentoring graduate and undergraduate researchers, and collaborating with multidisciplinary research teams. Depending on the candidate's expertise, research activities may involve cybersecurity risk assessment for construction technologies, secure digital twins, AI-enabled cybersecurity, cyber-physical systems, robotics and automation security, Building Information Modeling, technology integration, or other related topics that support the secure digitalization of the built environment. Applicants must hold a PhD in Civil Engineering, Construction Engineering and Management, Computer Science, Cybersecurity, Electrical Engineering, Robotics, Artificial Intelligence, Information Systems, or a closely related field by the anticipated start date. The applicant must also be no more than five years post receipt of the PhD. The ideal candidate will have a strong publication record, demonstrated research experience in one or more of the group's core research areas, and a proven ability to conduct independent, high-impact research. Experience in cybersecurity for cyber-physical systems, digital twins, BIM, AI and machine learning, robotics, or digital construction technologies is highly desirable. Strong programming and analytical skills, excellent written and verbal communication skills in English, and the ability to work effectively in interdisciplinary and multicultural research teams are essential. To be considered, all applicants must submit a cover letter, curriculum vitae, transcript of degrees, research statement, at least 2 recommendation letters, and sample of representative publications, all in PDF format. Applications will be accepted immediately and candidates will be considered until the position is filled. If you have any questions, please reach out to Borja García de Soto email: garcia.de.soto@nyu.edu. 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. Students are drawn from among the world’s best. They are bright, intellectually passionate, and committed to building a campus environment anchored in mutual respect, understanding, and care. The NYUAD undergraduate student body has garnered an impressive record of scholarships, graduate-school admissions, and other global honors. Graduate education is an area of growth for the University; the current graduate student population of over 100 students is expected to expand in the next decade as doctoral programs are developed. Working for NYUAD At NYUAD, we recognize that Abu Dhabi is more than where you work; it’s your home. In order for research staff to thrive, we offer a comprehensive benefits package. This starts with a generous relocation allowance; educational assistance for your dependents; access to health and wellness services; and more. NYUAD is committed to research staff success throughout the academic trajectory, providing support for ambitious and world-class research projects and innovative, interactive teaching approaches. Support for dual-career families is a priority.  Visit our website for more information on benefits for you and your dependents. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to the excellence and vibrancy of our academic community. Applications are welcome from all qualified candidates. In line with UAE regulations, Emirati candidates are encouraged to apply. Join NYU Abu Dhabi, an exceptional place for exceptional people. NYUAD values belonging and respect; such principles are fundamental to the university’s commitment to excellence. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to our vibrant, multidisciplinary research and teaching community. Multidisciplinary research and exceptional teaching in a global campus community are hallmarks of the University’s mission. @WorkAtNYUAD

Salary

Competitive

Posted

13 Jul 2026

Post-Doctoral Associate in the Division of Engineering (Electrical and Computer Engineering)

NEW YORK UNIVERSITY ABU DHABI

New York University Abu Dhabi Corporation

United Arab Emirates, Abu Dhabi

institution

New York University Abu Dhabi Corporation

United Arab Emirates, Abu Dhabi


Description The Clinical Artificial Intelligence Lab at NYU Abu Dhabi seeks to improve patient care by developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health records and medical images, for applications pertaining to patient diagnostics and prognostics. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection of computing and healthcare. Methodologies of interest include: multi-modal learning, foundation models, including large language models, agentic AI, multi-agent AI systems, transfer learning, self-supervised learning, and federated learning. The Postdoctoral Researcher will be primarily based at NYU Abu Dhabi. The researcher will report directly to Dr. Farah Shamout and work in close collaboration with other researchers, PhD students, and undergraduate research assistants. The researcher will engage with our regular collaborators across the NYU campuses and local medical institutions in the UAE. Key Responsibilities Research Support the supervisor in developing and implementing the research agenda; Conduct high-quality and innovative research primarily focused on ML methodology development for healthcare; Generate new high-impact ideas based on gaps and limitations of the state-of-the-art (SOTA); Design and implement experiments to compare proposed work with SOTA baselines; Publish research findings in high-impact journals and conferences; Communicate and present research findings at international academic gatherings; Create, maintain, and document high-quality research code for reproducibility; Maintain good practice in managing and accessing sensitive medical datasets; Assist the supervisor in the preparation of grant applications (as appropriate); And collaborate with scientists within the NYU Global Network and in Abu Dhabi. Training & professional development* Attend trainings and workshops for career development; Mentor PhD students and undergraduate research assistants (as appropriate); Actively participate in events and committees at NYU Abu Dhabi, such as the Postdoctoral Council Steering Committee; Gain experience in applying for local research grants (subject to eligibility); And transition to independence to pursue a career of choosing following the appointment. * The researcher will create a personalized training and development plan with the supervisor. Minimum Qualifications Currently has or is in the process of completing a PhD, MD/PhD, DPhil or equivalent terminal degree from a recognized institution (no more than 5 years since completing the doctoral degree) Doctoral research in the area of machine learning and artificial intelligence Bachelor’s/ Master’s degree in computer science, mathematics, computer engineering, or relevant technical field First-author peer-reviewed published papers (or under review) Proficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow) with several years of practice Experience in maintaining high-quality code on Github Experience in running and managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a team to get the work done Excellent communication skills (oral and written communication) Willingness to learn and confront new challenges Preferred Qualifications Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal learning, transfer learning, foundation models, and self-supervised learning. Experience in dealing with large medical datasets (e.g., electronic health records data or medical images) Ability to use high performance computing cluster For consideration, applicants need to submit a cover letter, curriculum vitae with full publication list, research statement (1-page), project proposal summary (1-page), a transcript or degree, and three letters of reference, all in PDF format. If you have any questions, please email Prof. Farah Shamout at farah.shamout@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 Dhab 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. Students are drawn from among the world’s best. They are bright, intellectually passionate, and committed to building a campus environment anchored in mutual respect, understanding, and care. The NYUAD undergraduate student body has garnered an impressive record of scholarships, graduate-school admissions, and other global honors. Graduate education is an area of growth for the University; the current graduate student population of over 100 students is expected to expand in the next decade as doctoral programs are developed. Working for NYUAD At NYUAD, we recognize that Abu Dhabi is more than where you work; it’s your home. In order for research staff to thrive, we offer a comprehensive benefits package. This starts with a generous relocation allowance; educational assistance for your dependents; access to health and wellness services; and more. NYUAD is committed to research staff success throughout the academic trajectory, providing support for ambitious and world-class research projects and innovative, interactive teaching approaches. Support for dual-career families is a priority. Visit our website for more information on benefits for you and your dependents. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to the excellence and vibrancy of our academic community. Applications are welcome from all qualified candidates. In line with UAE regulations, Emirati candidates are encouraged to apply. Join NYU Abu Dhabi, an exceptional place for exceptional people. NYUAD values belonging and respect; such principles are fundamental to the university’s commitment to excellence. NYUAD is an equal-opportunity employer. We welcome applications from all qualified candidates and seek individuals who will contribute to our vibrant, multidisciplinary research and teaching community. Multidisciplinary research and exceptional teaching in a global campus community are hallmarks of the University’s mission. @WorkAtNYUAD

Salary

Competitive

Posted

13 Jul 2026

Assistant Lecturer/Lecturer/Senior Lecturer in Clinical Psychology

UNIVERSITY OF THE SOUTH PACIFIC

University of the South Pacific

Fiji

institution

University of the South Pacific

Fiji


The University of the South Pacific (USP) is the premier tertiary institution in the Pacific region. Established in 1968, it is committed to international standards of research and teaching excellence, with an emphasis on key regional issues. USP is jointly owned by 12 member countries: Cook Islands, Fiji, Kiribati, Marshall Islands, Nauru, Niue, Samoa, Solomon Islands, Tokelau, Tonga, Tuvalu and Vanuatu. Courses are offered face-to-face at our main campuses (predominantly at Laucala Campus where this position is based), as well as by online and blended modes, in order to cater for students, spread across 33 million square kilometers of ocean, on both sides of the international dateline. This location at the heart of the world’s most linguistically diverse region makes USP a fascinating institution in which to work. The School In line with the USP Strategic Plan for innovative, industry-focused education and training, the disciplines within the School of Law and Social Sciences (SoLaSS) are undertaking a dynamic phase of programme review and development. The aim is to strengthen graduate outcomes by building programmes with a clear purpose: preparing students for industry, professional roles, and careers across the Pacific. As one of the largest schools at USP, SoLaSS has a growing research culture with real impact in the region. Its psychology offering is particularly strong, making USP the only university in the Pacific to offer a major in psychology at both undergraduate and postgraduate levels. Specific Duties An Assistant Lecturer / Lecturer / Senior Lecturer in Clinical Psychology will drive course and curriculum development and deliver impactful teaching, research, and supervision for undergraduate and postgraduate Psychology students in the Pacific. The role calls for significant adaptability, particularly in courses requiring the supervision of clinically based students, given the absence of high-end mental health facilities and dedicated funding agencies in the region. You will build quality postgraduate clinical psychology training materials and activities, and develop collaborative partnerships with external stakeholders, including government agencies and development partners working in health and mental health. The Person we Seek To be considered for this position, applicants must have: For the appointment at Assistant Lecturer Level; a postgraduate degree (Masters/PhD) in a relevant discipline; or in exceptional cases, to meet particular disciplinary requirements in line with international standards, a relevant postgraduate qualification or professional qualification with relevant industry or research experience. Other Minimum Qualification Requirements may be stipulated according to particular disciplinary requirements, following international standards. For the appointment at Lecturer Level; a PhD in the relevant discipline with relevant tertiary teaching and/or research experience; or in exceptional cases, a Master’s degree or professional qualification with relevant teaching experience or relevant industry/professional experience or a significant research profile. Other Minimum Qualification Requirements may be stipulated according to particular disciplinary requirements, following international standards. For the appointment at Senior Lecturer level a PhD in the relevant discipline with relevant tertiary teaching experience and/or research experience; or in exceptional cases, a Master’s degree or professional qualification with relevant teaching experience or relevant industry/professional experience or a significant research profile. For example, Profession-based disciplines; in addition, a Senior Lecturer will normally require a record of demonstrable scholarly and professional achievement in the relevant discipline. Other Minimum Qualification Requirements may be stipulated according to particular disciplinary requirements, following international standards  Enquiries and further information: myhr@usp.ac.fj; 3231000 The position is available for a term of five years and may be renewed by mutual agreement  

Salary

Assistant Lecturer: FJ$71,212 to FJ$85,454 per annum. Lecturer: FJ$90,493 – FJ$119,068 per annum Senior Lecturer: FJ$122,768 - FJ$141,655 per annum

Posted

14 Jul 2026

Upgrade Pathway Coordinator

UNIVERSITY OF SOUTHAMPTON

University of Southampton

United States, Southampton

institution

University of Southampton

United States, Southampton


USAIS – Upgrade Pathway Coordinator Join the University of Southampton Auditory Implant Service (USAIS) as an Upgrade Pathway Coordinator and make a meaningful impact on the lives of cochlear implant and auditory implant patients. We provide vital services for severely and profoundly deaf individuals across the south of England and the Channel Islands.  USAIS is a nationally recognised centre of excellence, providing specialist assessment, surgical intervention, and lifelong support for individuals with auditory implants. Our team is passionate about enhancing quality of life through cutting-edge technology and holistic care.  About the role: Location: University of Southampton Highfield Campus, Building 19  Working hours: Monday to Friday 9am-5pm  Job Purpose: To work with the Clinic Operational and Assistant Manager, Team Leaders and clinical staff, to ensure effective management of University of Southampton Auditory Implant Service (USAIS) patients through the Cochlear Implant (CI) & Bone Conduction Hearing Implant (BCHI) Upgrade Pathway What you will do: Manage and coordinate the purchase of newly implanted CI & BCHI patients processor technology Be responsible for ensuring every 5 years, patients progress through the upgrade pathway to replace their processor equipment with the latest technology Liaise with Clinical Team Leaders to manage and prioritise a high-volume caseload of upgrade patients, ensuring appropriate sequencing in line with clinical requirements, patient readiness, equipment availability, and service capacity  Ensure accurate and timely ordering of equipment through NHS Supply Chain (NHSSC), to align with patient upgrade due dates, monitor and track order status & delivery dates Goods receipt, unpack and prepare the processor kit and accessories for the patient appointment What you will bring: Relevant work experience within an administrative or customer support role, preferably in a healthcare setting or clinical environment – including NHSSC and Patient Administration System (PAS) Strong communication skills are essential, with a proven ability to prioritise and manage a busy workload  Excellent attention to detail, record keeping skills and maintenance of confidentiality for all data & patient information Strong teamwork skills and the ability to build positive working relationships  Ability to thrive and support colleagues in a busy, noisy working environment Special requirements: The maintenance of confidentiality in information and data management is mandatory & ability to cross-check data from multiple sources, with excellent attention to detail and accuracy  Working at UoS: We value equality, diversity, and inclusion, ensuring a supportive and inclusive environment  Enjoy a generous holiday allowance and additional university closure days  We support flexible working arrangements.  For more information about USAIS, visit our website. Informal Enquiries: Contact Cath Grimer 02380 593522 or c.grimer@soton.ac.uk Working at the University of Southampton: Check out the staff benefits and why you should join us at The University of Southampton. *An standard DBS check is required for this role.

Salary

£27,319 to £30,378 per annum

Posted

13 Jul 2026

Doctoral Researcher (PhD student) in Machine Learning

AALTO UNIVERSITY

Aalto University

Finland

institution

Aalto University

Finland


A Doctoral Researcher (PhD student) in Machine Learning for Electron–Phonon Interactions and Wannier-Based Hamiltonians Aalto University is where science and art meet technology and business. We shape a sustainable future by making research breakthroughs in and across our disciplines, sparking the game changers of tomorrow and creating novel solutions to major global challenges. Our community is made up of 16 000 students and 5 200 employees, including 446 professors. Our campus is in Espoo, Greater Helsinki, 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 School of Chemical Engineering (CHEM School) is one of the six schools of Aalto University. It combines natural sciences and engineering in a unique way. The Department of Chemistry and Materials Science is looking for: A Doctoral Researcher (PhD student) in Machine Learning for Electron–Phonon Interactions and Wannier-Based Hamiltonians The ELPH-ML project, led by Dr. Ransell D'Souza at the Department of Chemistry and Materials Science, Aalto University, and the Data-driven Atomistic Simulation (DAS) group, led by Prof. Miguel Caro at the Department of Chemistry and Materials Science, Aalto University, are jointly hiring a Doctoral Researcher. In this position, you will work on a project funded by the Research Council of Finland to build a machine learning framework linking electron–phonon interactions, Wannier-based Hamiltonians, and phonon properties for functional materials. You will work under the supervision of the Principal Investigator, Dr. Ransell D'Souza, and collaborate closely with Prof. Miguel Caro's group, whose core expertise is the development of machine-learning-infused atomistic modeling techniques and their application to important problems in chemistry, physics and materials science. Together, you will help advance a key scientific discipline that directly impacts important technological and societal topics such as thermoelectric energy harvesting and next-generation gas sensors. The project has access to state-of-the-art supercomputing facilities (CSC's Puhti, Mahti, and LUMI) and is well integrated within the international electronic-structure and machine learning communities. Informal inquiries about the position can be directed to Ransell D'Souza (rdsouza@sissa.it). Please read the description below in full before directly contacting us by email. Your role and goals You will develop data-driven and machine learning workflows to predict Wannier Hamiltonians, phonon properties, and electron–phonon coupling in layered transition-metal dichalcogenides (TMDCs) such as MoS₂, WS₂, MoSe₂, WSe₂, and WTe₂. For training the machine learning models, you will generate datasets from electronic structure theory calculations using Quantum ESPRESSO, Wannier90, and EPW. You will apply the developed E(3)-equivariant AI framework to quantify band-convergence effects on thermoelectric transport (Seebeck coefficient, conductivity, ZT) and to model gas adsorption effects (NH₃, CO, CO₂) relevant to next-generation 2D gas sensors. You will manage large-scale simulations run on world-class supercomputing facilities alongside AI algorithms and data analytics tools, and share your results with experimental collaborators. The position is part of the Research Council of Finland project ELPH-ML (https://research.fi/en/results/funding/88752). In combination with academic development courses at Aalto University, we will help you grow a competitive and international career profile. Your experience and ambitions We welcome candidates with a Master's degree in (computational) chemistry, physics, or materials science who are curious about applied machine learning in the natural sciences. Prior machine learning or Python experience is a strong bonus, but not a must. We seek colleagues who enjoy coding, scripting and analytics, and are keen to push the boundaries of data-driven materials science and machine learning in atomistic simulations. This project requires creative thinking and programming, as well as technical expertise in materials simulations, electron–phonon physics, and machine learning. We further appreciate willingness to travel, teach and mentor, collaborate and communicate science. To succeed in this role, you should have: A Master’s degree (or equivalent*) in Chemistry, Physics, Materials Science, Mathematics, Computer Science, or a related field. (*You are required to have a degree that would allow you to enroll for a PhD program in the granting institution, e.g., a 1st hons BSc in the UK is also eligible.) Prior programming experience, especially with Python. While you are not expected to be an expert programmer, some hands-on experience in programming is mandatory. Note that it will be entirely possible to develop more advanced programming skills during the doctoral studies. A strong interest in atomistic simulations, machine learning and scientific method and software development. Proficiency in English (written and spoken). (Preferred) Experience with any of the following: Electronic structure software (e.g., Quantum ESPRESSO). Molecular dynamics packages (e.g., LAMMPS). Machine learning interatomic potentials (e.g., GAP, MACE, NequIP ). Machine learning libraries and frameworks such as Scikit-learn, TensorFlow, or PyTorch, and e3nn_jax. If you have experience with other types of modeling tools (e.g., Boltzmann transport solvers, phonon codes like Phono3py/ShengBTE), please state it in your cover letter. Applicants must fulfill the eligibility and admission criteria for Aalto’s Doctoral Programme in Chemical Engineering as specified at Aalto Doctoral Programme in Chemical Engineering | Aalto University. If you feel you are interested and qualified for the position but are concerned about not fulfilling all the criteria, still feel free to apply. Take a look at this article in Forbes. What we offer Aalto’s Department of Chemistry and Materials Science is a leading research environment in Finland for computational chemistry and materials science, with four groups specializing in different branches (Soft Materials Modelling, Computational Chemistry, Inorganic Materials Modelling, and Data-driven Atomistic Simulation). The fixed term contract is initially for 2 years and during the first 6 months you must apply and receive a right to study in the doctoral programme. Aalto University follows the salary system of Finnish universities. The starting salary for Doctoral Researchers is 3142,65€ / month (gross). The contract includes Aalto University occupational healthcare benefits. The position will be filled as soon as a suitable candidate is identified. The starting date for the position is in the autumn 2026, but the exact date can be agreed with the selected candidate. The primary workplace will be the Otaniemi Campus at Aalto University. Ready to apply? To apply for the position, please submit your application no later than 31.08.2026 including the attachments mentioned below as one single PDF document in English through the link ’Apply now’ link at the bottom of the web page. Please note: Aalto University’s employees should apply for the position via our internal HR system Workday (Internal Jobs) by using their existing Workday user account (not via the external webpage for open positions). If you are a student or visitor at Aalto University, please apply with your personal email address (not aalto.fi) via Aalto University open positions. Letter of motivation (max 1 page): Include your name and email. Briefly motivate your interest in the position and explain how/to what extent you fulfill the requirements. Briefly mention any prior research experience you may have. Please, do not use ChatGPT or similar tools to prepare your cover letter for you. CV including list of publications (max 2 pages): personal and academic information, list of skills, projects, etc. Lying on your CV is immediate grounds for disqualification. If you are invited for an interview, you will be asked about information provided here. If you are eventually offered the position, you will be asked for a transcript of academic records. Contact details of at least two referees (or letters of recommendation, if already available) Applications sent via email will not be considered; only submissions through the online recruitment system are accepted. Questions about the vacancy may be directed via email to Dr. Ransell D'Souza rdsouza@sissa.it or Prof. Miguel Caro miguel.caro@aalto.fi. Please contact primarily project PI, D'Souza. Contact Prof. Caro only if Dr. D'Souza can’t be reached. More about Aalto University: Aalto.fi youtube.com/user/aaltouniversity linkedin.com/school/aalto-university/ www.facebook.com/aaltouniversity instagram.com/aaltouniversity To view information about Workday Accessibility, please click here. Please see more of our Open Positions here.

Salary

3142,65€ / month (gross)

Posted

13 Jul 2026

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