Senior Research Officer

* Generous salary packaging to save you income tax on your wages thereby boosting your monthly take home pay (max. $15,900 general expenses + $2,650 meals/accom)* Ample opportunities for on-going training and development* Stimulating, diverse and highly international research environment* Flexible work arrangements e.g. start / finish times* 18 weeks paid parental leave for both parents including paid superannuation* A range of additional leave types to meet your personal needs including cultural leave, conference leave, community service and study leave* Discounted Health Insurance* Lifestyle discounts with our community partners* PhD in immunology, functional genomics, molecular biology, or a related discipline, with a publication record demonstrating strong experimental and conceptual expertise.* Deep knowledge of human immune cell biology, including cellular differentiation, activation pathways, cytokine signalling, and immune effector functions.* Hands-on experience with immune functional assays, such as stimulation/activation assays, cytokine profiling, co-culture systems, flow cytometry, intracellular staining, and readouts of immune cell state and function.* Experience isolating and working with primary human immune cells (e.g., PBMCs, T cells, B cells, monocytes, NK cells), including culture, perturbation, and phenotyping.* Ability to design mechanistic experiments that link genetic variation to immune regulatory pathways, integrating computational predictions with biological models.* Familiarity with single-cell genomics (scRNA-seq, scATAC-seq), genome engineering (CRISPR), or high-throughput molecular profiling, and the ability to apply these tools in targeted, hypothesis-driven ways.* Demonstrated ability to collaborate effectively with computational biologists, interpret statistical genetics and single-cell discovery outputs, and translate them into functional follow-up.* Strong analytical and problem-solving skills, with the ability to independently drive multi-step mechanistic studies from concept through to validation.* Exceptional attention to detail and rigorous experimental discipline, ensuring reproducibility across complex cell-based experiments.* Strong organisational skills, including the ability to manage multiple immune-focused projects and experimental timelines.* Excellent written and verbal communication skills, with the ability to present immunology-focused findings to multidisciplinary scientific teams.* Motivation to learn new technologies, including emerging single-cell, multi-omic, and genome engineering methods relevant to immune function and therapeutic discovery.* Familiarity with disease-relevant immune models, such as autoimmune T cell activation, chronic inflammation, infection-mimicking stimuli, or dysfunctional myeloid states.* Experience with high-parameter flow cytometry, spectral flow, mass cytometry, or advanced immune phenotyping platforms.* Experience integrating computational predictions into experimental strategy, including working with eQTL/caQTL data, target nomination lists, or genotype-linked cellular phenotypes.* Expertise in cell signalling and intracellular pathway analysis, including phospho-flow, reporter assays, or multiplex protein readouts.* Understanding of drug target biology, therapeutic mechanisms, or early-stage translational discovery workflows.* Experience working in multidisciplinary teams, especially across computational biology, genomics, immunology, and clinical collaborators.* Prior involvement in IP generation, technology development, or industry-facing research partnerships, particularly in immunology or functional genomics.* Experience supervising junior researchers or technical staff, supporting experimental planning, troubleshooting, and analytical interpretation.* Familiarity with regulatory considerations around human samples, including ethics, biobanking, and data governance.**Strong communication skills** – able to explain analytical approaches clearly to both computational and experimental colleagues.#J-18808-Ljbffr