Instituto Federal de Minas Gerais

The University of Vienna is a community of almost 11,000 individuals, including approximately 7,700 academic staff members, who passionately pursue answers to the profound questions that shape our future. They represent individuals driven by curiosity and a relentless pursuit of excellence. With us, they find the space to try things out and unfold their potential. Are you inspired by their passion and determination? To strengthen our team, we are seeking a university assistant to develop advanced machine learning and artificial intelligence methods. University assistant predoctoral - PhD position in Probabilistic and Interactive Machine Learning 39 Faculty of Computer Science Startdate: 01.10.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc) Limited until: 30.09.2030 Reference no.: 5376 Your personal sphere of influence: The working group “Probabilistic and Interactive Machine Learning” within the research group “Data Mining and Machine Learning” at the Faculty of Computer Science, led by Prof. Sebastian Tschiatschek, develops foundational methods in machine learning and artificial intelligence. We focus particularly on the areas of reinforcement learning, interactive learning, and deep probabilistic models. While modern reinforcement learning (RL) has achieved remarkable success, it remains limited when applied to complex, open-ended, or poorly defined environments. Two of the most critical bottlenecks in contemporary AI are sample inefficiency, often caused by the lack of intelligent, structured exploration, and the "reward engineering" problem, where designing an explicit scalar reward function that captures desired behavior is incredibly difficult or impossible. Furthermore, as AI systems are deployed in more complex environments, the challenges of AI alignment (ensuring systems behave according to human preferences) and constrained learning (adhering to strict safety, legal, or physical boundaries) become important. This position is dedicated to addressing these core challenges by advancing the frontiers of Inverse Reinforcement Learning (IRL), exploration, and safe/aligned AI.                       Your future tasks: You actively participate in research, teaching & administration, which means: You will contribute to academic research projects in the above-mentioned areas. You will work on scientific articles and publish your research results. You will participate in academic conferences to present your research. We expect you to conclude your dissertation agreement within 12 months. You will work on your dissertation and bring it to completion. You will take on teaching responsibilities as specified by the collective agreement. You will support the supervision of students’ projects and theses. You will undertake administrative duties in research, teaching, and university administration, and support the organization of workshops, conferences, and symposia. This is part of your personality: Completed Master's degree (or comparable degree) in computer science, data science, mathematics, communication engineering, or a related field (Applications from candidates close to completion are welcome. Employment can only begin once the Master´s degree has been awarded.) Excellent command of English Outstanding written and oral communication skills Strong ability to collaborate within research teams Perseverance and a proven ability to bring projects to reliable completion High motivation and commitment to scientific excellence Willingness to travel, including participation in national and international conferences Solid knowledge of machine learning and artificial intelligence (in particular in the areas of bandits and reinforcement learning) Strong programming skills, preferably in Python. Experience with deep learning frameworks such as Jax, PyTorch, or TensorFlow. Excellent analytical skills and strong interest in developing a deep understanding of algorithms and methods Cooperative, team-oriented, and proactive working style The following are also desirable: Experience with research methods in the field of machine learning and artificial intelligence, as well as scientific writing Excellent academic record, ideally with initial research results in the area of the position, documented by publications or manuscripts in preparation Experience in university teaching International experience What we offer: Work-life balance: Our employees enjoy flexible working hours and can partially work remotely.  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 is easily accessible by public transport. Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge. Fair salary: The basic salary of EUR 3.776,10 (on a full-time basis) increases if we can credit professional experience. Tenure: 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. It is that easy to apply: Academic curriculum vitae  Letter of motivation including your project ideas (and description of your teaching experience, if available) Abstract of Master´s Thesis Degree certificates Transcript of records List of publications, evidence of teaching experience (if available) If you have any questions, please contact: Sebastian Tschiatschek sebastian.tschiatschek@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: 06/06/2026 Prae Doc

Posting Start Date: 21/04/2026 Schemes of Service: Research Division: Engineering Employment Type: Fixed Term About the Project We are seeking a highly motivated Research Engineer to spearhead a pioneering project involving the integration of a high-precision surveyor tool (Trimble S9 HP total station) onto a dynamic legged robot. This project moves beyond standard mechanical integration, focusing heavily on the software architecture required for seamless, automated operation. The core objective is to architect and develop the robust middleware that facilitates real-time communication between the legged robot's controller and the sophisticated surveying payload. By taking on this role, the successful candidate will master the art of payload integration and middleware development—a highly sought-after skillset that empowers engineers to upgrade, integrate, or automate virtually any tool or sensor payload in their future careers. Key Responsibilities Middleware Development: Architect, build, and maintain the communication middleware bridging the legged robot's control system and the surveyor payload. Systems Integration: Ensure seamless hardware and software integration between the mobile base and the high-precision surveying equipment. Mapping & Navigation: Implement and optimize mapping algorithms and remote control functionalities tailored for a legged platform navigating complex terrains. Protocol Implementation: Utilize robust industrial communication protocols and custom scripts to ensure reliable data transfer and command execution. Testing & Validation: Design and execute rigorous field testing procedures to validate the integrated system's accuracy, stability, and reliability. Qualifications & Requirements Bachelor’s degree in Robotics Systems Engineering, Mechatronics, Computer Science, or a closely related field. (Graduating students finishing coursework by April are highly encouraged to apply). Strong foundational knowledge of legged robotics, including locomotion, kinematics, and control systems. Proven proficiency in robotics middleware (e.g., ROS/ROS2) and related communication frameworks. Hands-on experience with mapping technologies (SLAM) and remote operation systems. Strong programming skills, particularly in Python and C++. Familiarity with industrial protocols and serial communication. A proactive mindset with the ability to troubleshoot complex electro-mechanical and software integration challenges. Why Join This Project? Gain hands-on experience with cutting-edge legged robotics and top-tier industrial surveying equipment. Develop highly transferable skills in systems integration that will set you apart in the robotics and automation industry. Work in an innovative academic research environment with opportunities to define the architecture of a novel automated system.

Full time 2 year fixed term contract available with the possibility of extension Work on a project focuses on improving care for people with osteoarthritis Base Salary starting from $113,400-$151,328 + 17% superannuation About the opportunity The Sydney School of Health Sciences is experiencing significant growth and investment as part of the Faculty of Medicine and Health's strategic vision. We are seeking a Level A or B Research Associate/ Fellow with expertise in implementation research that includes quantitative and qualitative methods, to assist in research that will evaluate a targeted strategy to support health professionals in delivering more effective, evidence-based care for knee osteoarthritis, with the aim of reducing low-value treatments and improving patient outcomes. This project focuses on improving care for people with osteoarthritis, a common and painful condition that costs the Australian healthcare system over $4 billion each year. Although the most effective treatments involve education, exercise and weight management, many patients are not offered these options and instead receive unnecessary imaging or are referred for surgery that may not benefit them. We are seeking a highly motivated academic Research Associate/Fellow (Level A or B) to lead and coordinate key elements of a complex health research trial. In this role, you will establish and manage governance and stakeholder groups while leading protocol development and contributing to data acquisition, analysis and management. The position involves engaging with a wide range of stakeholders-including GPs, physiotherapists, primary health networks, and local healthcare providers-to support trial activities. You will lead co-design workshops and implementation strategy development, oversee pilot and full trial delivery, drive process evaluation activities and supervise junior staff, including a PhD student and data analyst. Your key responsibilities will be to: Establish and manage key governance and advisory groups, including steering committees and advisory panels lead the development of the trial protocol prepare and coordinate ethics and governance submissions and oversee trial registration oversee trial database design and setup, ensuring alignment with study requirements work closely with the study statistician on developing and implementing the randomisation schedule and statistical analysis plan. oversee the recruitment of participants (health professionals and consumers) to the trial build and maintain strong relationships with stakeholders, including GPs, physiotherapists, Primary Health Networks (PHNs), and local providers to support recruitment and engagement lead co-design workshops and facilitate the development and refinement of implementation strategies with clinicians and consumers oversee the delivery of the pilot phase and full trial implementation oversee and deliver education and engagement activities, including webinars, site visits, and academic detailing sessions drive the trial process evaluation activities, including recruitment, data collection, analysis, and reporting, ensuring continuous improvement and successful trial outcomes supervise and support junior team members, including a data analyst and PhD student. About you A postgraduate qualification (PhD or equivalent) in health sciences, public health, epidemiology, or a related discipline demonstrated experience in designing, managing, and delivering complex health or implementation research projects, ideally including clinical or cluster randomised trials strong knowledge of research governance processes, including preparation and submission of ethics and regulatory approvals experience in protocol development, trial registration, and working with data systems or databases in a research setting proven ability to collaborate with statisticians and analysts, with an understanding of study design, randomisation, and data analysis methods (including mixed methods or process evaluations) experience supervising or mentoring research staff and/or students (e.g. data analysts, PhD candidates) demonstrated stakeholder engagement skills, with experience working with healthcare professionals (e.g. GPs, allied health), health networks, and/or community groups experience leading workshops, co-design activities, or implementation strategy development with diverse stakeholders strong project management skills, including the ability to coordinate multiple activities, meet deadlines, and oversee trial delivery from pilot through to completion excellent written and verbal communication skills, including developing stakeholder materials (e.g. audit and feedback reports) and delivering presentations, webinars, or training sessions experience in both qualitative and quantitative research methods, including data collection, analysis, and reporting for process evaluations familiarity with Australian healthcare systems and data sources (e.g. National Health Services Directory) is highly desirable. Sponsorship / work rights for Australia You must have unrestricted work rights in Australia for the duration of this employment to be eligible to apply. Visa sponsorship is not available for this appointment. Pre-employment checks and declarations Your employment is conditional upon the successful completion of all pre-employment or background checks required for the role in terms satisfactory to the University. Also, to meet the University's obligations under the National Higher Education Code to Prevent and Eliminate Gender-Based Violence you will be asked to declare if you have been investigated for, or found to engaged in, sexual harm or gender-based violence in the course of previous employment or in a legal process. Similarly, your ongoing employment is conditional upon the satisfactory maintenance of all relevant clearances and background check requirements. If you do not meet these conditions, the University may take any necessary step, including the termination of your employment. As this position is located on an NSW Health site, it is a regulatory requirement to complete compulsory employment checks prior to starting in this position. For more information and instructions, please visit: NSW Health employment requirements This position is designated as involving child-related work. To undertake or remain in this position, you are required to apply for and obtain a Working with Children Check clearance in accordance with the Child Protection (Working with Children) Act 2012. EEO statement At the University of Sydney, our shared values are trust, accountability and excellence and we strive to be a place where everyone can thrive. We are committed to creating a University community that thrives through diversity and reflects the wider community that we serve. We deliver on this through our commitment to diversity and inclusion, evidenced by our people and culture programs, as well as key strategies to increase participation and support the careers of Aboriginal and Torres Strait Islander People, women, people living with a disability, people from culturally and linguistically diverse backgrounds, and those who identify as LGBTQIA+. We welcome applications from candidates from all backgrounds. We are proud to be recognised as an Australian Workplace Equality Index (AWEI) Platinum Employer. Find out more about our work on diversity and inclusion. How to apply Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page. To submit an application for this role please provide the following information: A cover letter which includes a written response to selection criteria addressing your ability to meet the requirements outlined above within the context of the key responsibilities of the role (maximum 1000 words). Your current CV or resume, including two referees. Please ensure your cover letter is clear, concise, addressing the selection criteria and states the type of employment and level in which you are applying. For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply. For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Rachel Ann Yazigi Recruitment Operations by email to rachel.yazigi@sydney.edu.au. © The University of Sydney The University reserves the right not to proceed with any appointment. Click to view the Position Description for this role. Applications Close Sunday 21 June 2026 11:59 PM