Universidade Fernando Pessoa

Part Time 6 month fixed term opportunity for a Research Assistant Join a high-performing, multidisciplinary Computational Neuroimaging team dedicated to the ongoing development of novel imaging biomarkers for Multiple Sclerosis Base Salary HE04 $83,038 or HE05 $89,755 + 17% superannuation, based on experience About the opportunity Multiple Sclerosis (MS) affects more than 2.9 million people worldwide and is the leading non-traumatic cause of neurological disability in young adults. In Multiple Sclerosis, not all white-matter lesions are equal - some contribute disproportionately to long-term disability while others remain clinically silent. We hypothesis that a subset of MS lesions, jointly characterised by their degree of axonal loss and anatomical location, can substantially improve prediction of clinical progression. The project is aiming to develop a novel lesion classification framework that using routinely acquired clinical MRI. You will join a high-performing, multidisciplinary Computational Neuroimaging team dedicated to the ongoing development of novel imaging biomarkers for Multiple Sclerosis, bridging the gap between advanced computational methods and real-world clinical impact. The team operates in a leading-edge environment that sits at the intersection of medical imaging, data science, and clinical neurology. We are committed to the clinical translation of imaging metrics, with a specific focus on improving the lives of individuals with Multiple Sclerosis (MS). You will be joining our multidisciplinary team, contribute to the ongoing development of novel imaging biomarkers for multiple sclerosis. Your key responsibilities will be to: neuroimaging Pipeline Management: implement and maintain automated MRI preprocessing and analysis pipelines for large-scale, multi-site clinical datasets. advanced Lesion Analysis: Implement lesion segmentation and characterisation techniques using structural, diffusion, and quantitative MRI. data Management: Oversee the curation and quality control of the training and validation dataset machine Learning Development (HEO5): implement model training to classify lesion severity and map anatomical connectivity. Build and validate predictive models to establish the relationship between imaging metrics and longitudinal clinical disability. About you Essential: academic Qualifications: Bachelor's in biomedical engineering, Computer Science, Medical Image Analysis, Applied Statistics, or a related quantitative discipline. (Current enrolled HDR students are also encouraged to apply) imaging Expertise: Demonstrated experience in MRI quantitative analysis, experience with structural diffusion-weighted (dMRI) is preferable (HEO5) software Proficiency: Expert command of industry-standard neuroimaging toolkits (e.g., FSL, FreeSurfer, ANTs, MRtrix3) data Handling: Proven ability to manage, curate, and perform quality control on large-scale, multi-site neuroimaging datasets programming Proficiency: Proficiency in Python, including the ability to automate pipelines and manage version control (Git) and data science libraries scientific Communication: Demonstrated ability to draft high-quality technical reports and manuscripts for peer-reviewed journals problem Solving: A proactive approach to troubleshooting complex computational pipelines and data inconsistencies collaborative Mindset: Experience working within multidisciplinary teams, specifically the ability to communicate technical concepts to non-technical clinical stakeholders (Neurologists/Radiologists) time Management: Ability to work independently and meet project milestones within a fast-paced research environment. Desirable: deep Learning: Experience with frameworks such as PyTorch or TensorFlow applied to medical image analysis AI Analytic Foundations (HEO5): Solid understanding of machine learning principles and high-level statistical modelling for predictive analytics. Translational Interest: A genuine interest in clinical biomarker validation and the desire to see research outputs impact patient care. To keep our community safe, please be aware of our COVID safety precautions which form our conditions of entry for all staff, students and visitors coming to campus. 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. 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. 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 Danielle Selinger Recruitment Consultant by email to danielle.selinger@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 Thursday 25 June 2026 11:59 PM

Health and Social Sciences Cluster Singapore Institute of Technology We are seeking a motivated and capable Research Assistant to join an exciting translational research project on spinal sarcopenia in older adults, with a focus on muscle degeneration, senescent progenitors, and regenerative failure. This role offers a unique opportunity to work across clinical research, functional assessment, imaging analysis, and laboratory investigation in a multidisciplinary academic environment. The successful candidate will support a funded research project that aims to generate clinically relevant insights into ageing, muscle health, and spine-related conditions. This is an excellent opportunity for candidates who are passionate about meaningful research and wish to build strong experience in applied human and translational studies. Key Responsibilities Support the Principal Investigator and research team in the implementation and coordination of the project Assist with participant recruitment, scheduling, follow-up, and study administration in accordance with approved ethics protocols Conduct and document functional assessments and study-related data collection Retrieve, organise, and manage imaging data, and assist with image-based analysis Support laboratory workflows such as tissue handling, histology, immunofluorescence, qPCR, ELISA, and related analyses Maintain accurate databases, study records, and project documentation Assist with literature review, data cleaning, preliminary analysis preparation, reporting, and regulatory submissions Coordinate procurement of reagents, consumables, and research-related items Ensure compliance with laboratory safety, biosafety, and institutional research governance requirements Job Requirements Bachelor’s degree in biomedical science, life sciences, physiotherapy, diagnostic radiography, medical laboratory science, or a related discipline Strong interest in translational, musculoskeletal, ageing, or clinical research Experience in clinical research coordination, patient-facing data collection, imaging analysis, or laboratory techniques will be advantageous Familiarity with histology, microscopy, immunofluorescence, molecular assays, or tissue-based workflows is preferred Good written and verbal communication skills Strong organisational skills, attention to detail, and professionalism Proficiency in Microsoft Office; familiarity with ImageJ, SPSS, STATA, or equivalent tools is an advantage Key Attributes Motivated, responsible, and able to work independently Careful and accurate in handling data, samples, and documentation Strong team player who can work effectively with academic, clinical, and student collaborators Willingness to learn and adapt in a dynamic multidisciplinary research environment Why Join Us This role offers valuable exposure to clinically relevant translational research with opportunities to develop experience in human studies, imaging, laboratory science, and multidisciplinary collaboration. The successful candidate will contribute to a meaningful project with real-world healthcare relevance while building a strong foundation for future research or postgraduate opportunities. Contract Type 1-year contract Work Location Singapore Institute of Technology, with project activities at SIT and partner sites as required.

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. The primary responsibility of this role is to deliver on an industry funded research project where you will be part of the research team to develop advanced Nuclear Quadrupole Resonance (NQR) scanning technologies. Job Responsibilities Participate in research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met. Undertake these responsibilities in the project: i. Conduct comprehensive literature review on NQR technology, including design approaches, scanning methods, signal processing techniques, and comparison with alternative detection technologies. ii. Support design and development of NQR prototype, including system architecture, component selection, and experimental setup. iii. Conduct lab and site tests to evaluate the performance of NQR prototype. iv. Generate design documents and test documents at every stage of development until the final prototype. Coordinate procurement and liaison with vendors/suppliers. 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 Has a bachelor’s degree in Electronics; Specialization in RF/Microwave or Digital Signal Processing (DSP) is preferred. Has solid knowledge of electronics, including circuit design, PCB layout, and hardware troubleshooting. Has relevant competence in the areas of Radio Frequency design and measurement; Familiarity with high-power amplifier systems is a plus. Has relevant experience in the areas of Digital Signal Processing (DSP) design and implementation is a plus. Experience in electromagnetic simulation using CST Studio Suite and circuit simulation with PSpice, LTspice, or equivalent is an advantage. Experience with developing software for instrument control and data acquisition using LabVIEW is helpful. Key Competencies Strong experimental skills and theoretical knowledge in electronic circuits, and RF or DSP design, with the ability to apply hands-on prototyping and system development. Able to build and maintain strong working relationships with people within and external to the university. 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