Massachusetts Institute of Technology

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. Key Responsibilities Participate in and manage the research project with the Principal Investigator (PI), co-PIs, research team and industry partners to ensure all project deliverables are met. Conduct insights-driven evaluations of existing QA/QC testing practices and identify opportunities to enhance efficiency and reduce redundant testing while maintaining compliance. Curate, standardize and integrate historical and statistical data to form the foundation of a structured database for construction QA/QC and traceability. Design and implement a digital chain-of-custody framework that captures assurance records including mill certificates, fabrication data, inspection results and carbon footprint information. Develop, train and validate AI models to automate QA/QC processes, enabling real-time verification, anomaly detection and consistency checks across records. Develop a cloud-based verification platform for digital data collection and real-time analytics. Develop and apply non-destructive testing (NDT) methods and data-driven approaches to determine material properties of reclaimed steel. Investigate geometric imperfections, accumulated deformations, and their impact on structural performance, particularly for compression members. Develop data-driven reusability assessment platforms integrating NDT data, machine learning models, and RFID-enabled traceability systems. Prepare and draft technical reports, conference/journal papers, and presentation materials; present research findings to internal reviews, industry partners and stakeholders. Engage with industry stakeholders throughout development, testing and refinement to ensure alignment with real-world requirements. To communicate in any relevant internal or external stakeholders to ensure project deliverables are met. Any ad-hoc duties assigned by Supervisor.  Job Requirements Master’s degree in Computer Science, Data Science, Civil/Construction Engineering, Engineering Systems or equivalent. Strong foundation in data engineering, AI/ML development, and software systems (e.g., data pipelines, cloud services, dashboards, web-based application development). Experience in handling real-world datasets and model development/deployment workflows. Domain expertise in building construction/civil/structural engineering, including familiarity with building management systems, software integration, data collection and analysis. Knowledge of construction QA/QC and quality control workflows (e.g., inspection processes, test documentation, traceability and compliance records) is an advantage. Strong background in structural engineering, structural mechanics, or steel structures. Familiarity with non-destructive testing (NDT) techniques for structural materials is desirable. Experience with structural modelling and analysis tools (e.g., finite element modelling, structural simulation) is desirable. Good interpersonal, written and verbal communication skills, with the ability to work independently and in multidisciplinary teams. Strong analytical and conceptual abilities; able to work both in a team and independently. Able to work under pressure and meet deadlines. Key Competencies Proficient in Python or other equivalent programming languages. Strong foundation in data analytics and data-driven modelling. 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.

At the University of Vienna almost 11,000 personalities work together towards answering the big questions of the future. Around 7,700  of them do research and teaching, around 3,000 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate 51 Faculty of Physics Startdate: 01.05.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.04.2030 Reference no.: 5504 How can we perform table-top experiments to obtain new insights into the foundations of quantum physics? Can we measure gravitational effects on entangled photons for shining light onto the interface of quantum physics and gravity? Can we exploit quantum photonics technology for novel quantum machine learning, quantum computing and quantum cybersecurity applications? Can we scale up multiphoton platforms by using integrated optics, quantum-dot single-photon sources and customized two-dimensional nonlinear materials? Such questions are the driving force behind our research. You will be part of our team and develop new ideas, technologies and experiments. Your personal sphere of influence: As a university assistant (PraeDoc) on this 4-year position, you will be part of the research group “Quantum Information Science and Quantum Computation”, led by Univ.-Prof. Dr. Philip Walther. The group is part of the Quantum Optics, Quantum Nanophysics & Quantum Information group at the Faculty of Physics, and a member of the Vienna Center for Quantum Science and Technology (VCQ) – one of the largest quantum hubs in Europe – and the Austrian Cluster of Excellence quantA. The group’s research combines the development of scalable photonic quantum technology for quantum computing and other quantum information applications with the investigation of fundamental quantum science questions.The main activities range from quantum control of single photons using solid-state photon sources, integrated waveguide technology, tailored nonlinear media and detectors based on superconductor technology to interferometric precision measurements of weak gravitational forces. You will also benefit from being a fellow of the Vienna Doctoral School in Physics (VDSP), being part of a thriving community with more than 100 quantum scientists on the premises, about 300 quantum researchers in Vienna. The Walther Group unites an international team of scientists who are passionate about research in quantum optics, quantum information and quantum technologies. Our 35 researchers, from undergraduate student and PhD candidate to postdoc, are working together on mostly experimental topics in small subgroups. Teamwork is a key factor in our group’s success. Together we have assembled a unique skill set and knowledge base in quantum information, quantum computation, quantum communication, quantum foundations as well as the quantum-gravity interface. Your future tasks: Active participation in research, teaching & administration, which means: You are involved in a specific and well-funded research project dedicated to experimental quantum optics in 2D materials. 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 contribute to teaching (lab courses, 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 contribute to outreach by publications, conference presentations and public activities. This is part of your personality: You have completed your Master's degree or Diploma in Physics and written your thesis in the field of quantum optics or nonlinear optics in ultra-thin materials. You have experience with table-top experiments, photonic platforms, optical non-linear processes, quantum optics and ultra-thin 2D materials. You have experience in academic writing. You should have experience with the usual tools for advanced experiments: programming experience: MATLAB, Python, LaTeX. You have excellent command of written and spoken English. What we offer: Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment. Good public transport connections: Your workplace in the center of beautiful Vienna is easily accessible by public transport. Potential for development: Success in life depends on what you make of it, but if you are ambitious and successful, there are plenty of opportunities to connect you to all relevant top research groups in the world. 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(40h/w, 14x p.a.) increases if we can credit professional experience. The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 4 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration. Equal opportunities for everyone: We look forward to diverse personalities in the team! It is that easy to apply: Your scientific curriculum vitae  A letter of motivation  Your bachelor's and master's degrees Title and abstract of your master's thesis Contact details of 2 references If you have any content questions, please contact: Philip Walther philip.walther@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 place particular emphasis on enhancing women’s representation among the academic and general university staff, particularly in leadership roles, 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: 04/25/2026  Prae Doc

Technical Manager (Finance) in the Department of Finance The Technical Manager (Finance) will provide support to researchers in assessing the feasibility and logistics of running their papers or in collecting primary as well as secondary data. The Technical Manager will help acquire and maintain servers for digital data infrastructure and also support researchers in accessing and using university resources efficiently, e.g., preparing customised data sets for secondary analysis or help onboarding researchers to high-performance financial computing facilities. The role holder will explore potential for linkages to other research and data hubs on the administrative and programme levels on a regular basis. There will be opportunities for the Technical Manager to engage with exciting topics in contemporary finance, e.g., in asset pricing, banking, corporate finance, quantitative risk management, climate finance, financial technologies, to enhance their ability to work with finance colleagues across a broad spectrum of topics.