Research Assistant - Bioinformatics @ The Garvan Institute of Medical Research

Employer : The Garvan Institute of Medical Research

Closing date:   31/01/2025


Brief position description:
  

The Garvan Institute of Medical Research brings together world leading researchers and clinicians, collaborating locally and globally, to improve human health. Our mission is to harness all the information encoded in our genome to better diagnose, treat, predict and prevent disease. From the individual patient with rare disease, to the many thousands affected by complex, widespread illness, we are pioneering discoveries across diseases that have the deepest impact on our community.

THE OPPORTUNITY

The Research Assistant is accountable for assisting with bioinformatic analysis of experiments conducted within the Swarbrick Laboratory, with strategic guidance and training from postdoctoral bioinformaticians in the Swarbrick Laboratory. 

The Swarbrick lab are global leaders in the application of cellular genomics to human cancer, to find new diagnostics and treatments for society’s most challenging cancers. We are a diverse multidisciplinary team of scientists and clinicians with a vision to change cancer medicine. More information can be found at https://smex-ctp.trendmicro.com:443/wis/clicktime/v1/query?url=www.swarbricklab.com&umid=52579d93-0c41-4689-a76b-4ae6dc2c81c1&auth=6ee66d642a212b82964c9073f0dd934b55317413-2f84ee924ff4634f3edf2dda9095e8194c21fa36

Major projects include generation of an international, large-scale, multi-omic breast cancer atlas and understanding the cellular mediators of response to cancer immunotherapy in breast cancer, prostate cancer and melanoma. The Laboratory is generating substantial single-cell sequencing (scRNA-Seq), spatial transcriptomics and other genomic and proteomic datasets from clinical samples and preclinical models. The RA will be actively working on the integration of these large multi-omic datasets and developing scalable, robust, cloud-based computational frameworks. The RA will learn and apply advanced methods in AI and Machine learning.

This role will suit a computational science/bioinformatics graduate with training and experience in advanced computational techniques and with an interest in cancer biology, spatial molecular biology or cellular genomics.


Salary: Up to $99,000 + 14% superannuation + salary packaging (depending on experience)

Employment Type: 2 year term contract with possibility to extend 


SNAPSHOT OF BENEFITS

- 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


WHAT YOU WILL DO

- Developing, maintaining and executing bioinformatic pipelines/workflows, particularly in relation to scRNA-seq and spatial transcriptomic data
- Contribute to the existing codebase in collaboration with other team members, including debugging, refactoring and enhancing legacy code
- Document new code, and make improvements to existing documentation
- Track, archive and actively manage raw and processed data in accordance with established procedures and policies
- Analyse clinical and experimental data, with an emphasis on relevance to clinical translation
- Assist other team members with their analyses
- Adopt, test and benchmark analytical packages for incorporation into analyses and standardised pipelines
- Present results internally and externally


ABOUT YOU

Essential Knowledge and Skills: 
- BSc or MSc in computer science or a quantitative discipline (Computational Biology, Bioinformatics, Mathematics and Statistics, Physics, Software Engineering, or a related field)
- Experience with version control systems, particularly Git
- Experience using R and/or Python programming language
- Familiarity with the Unix command line and high-performance computing environments and/or cloud computing

Desirable Knowledge and Skills:
- Knowledge of the fundamentals of molecular biology: DNA transcription and translation
- Experience in the analysis of large molecular datasets, such as whole genome and transcriptomic sequencing data
- Experience in handling, processing, and interpreting large-scale biological datasets derived from scRNA-seq and spatial technologies, such as Visium or Xenium, would be particularly beneficial
- Experience working in a multidisciplinary team
- Appreciation of ethical dimensions of clinical research

Personal Qualities: 
- Excellent communication skills for written reports and oral presentations
- Excellent organisational and time management skills
- Strong desire to work co-operatively with other team members
- Commitment to data organisation and implementation of quality controls
- An interest in understanding how cancers evolve and progress

HOW TO APPLY

To apply for this position, please submit your application with a CV and cover letter as one document, stating why you are interested in this role. We are reviewing applications as they are received. If you think you’re the right person for this role, we’d love to hear how your capabilities, achievements and experience set you apart. Only applicants with full working rights in Australia are eligible to apply for this role. Please refer to our careers page to apply for this position. 

Job website:  https://garvan.wd3.myworkdayjobs.com/en-US/garvan_institute/details/Research-Assistant---Bioinformatics_PRF7434

Contact name:  Orianna Peppas

Contact email: o.peppas@garvan.org.au

Data Science Hub Statistician @ Sydney Precision Data Science Centre, University of Sydney

Employer : Sydney Precision Data Science Centre, University of Sydney

Closing date:   27/01/2025


Brief position description:
  

We are currently seeking to appoint five research focused roles to work in the Data Science Hub at the Charles Perkins Centre. The Data Science Hub is a collaborative platform funded by the Charles Perkins Centre, Faculty of Medicine and Health, and Faculty of Science, to increase the capacity in data-intensive research with direct translational impact in biomedical and metabolomics health, public health and beyond. The Data Science Hub will enable context-specific data analysis on collaborative projects as well as enable the successful individuals to build their own independent careers in this exciting area. The Research Associate / Senior Research Fellow roles will be integral to the establishment of the Data Science Hub and will have an opportunity to work at the Charles Perkins Centre, with its diverse community of experimental scientists, preclinical researchers, experts in wearables data, epidemiology and data linkage, social scientists with access to large datasets associated with each area. 


The Charles Perkins Centre is a multidisciplinary centre and a world leader in its unique approach to bringing together and aligning the University of Sydney’s many disciplines to find solutions to and advance our knowledge and understanding of obesity, diabetes and cardiovascular disease and related conditions, their causes and societal impacts. This creative approach aligns depths and strengths to find solutions to the growing pandemic of metabolic disease. 

Your key responsibilities in addition to driving your research program, will be to: 
- establish and build analytical capacity of the Data Science Hub associated with large biobank repositories, multi-omics platforms, molecular epidemiology and multi-modality integration including and not limited to imaging, nutrition and wearables data, and establish a workflow for the processing, integration, and curation of Biobank, and inhouse data 
- facilitate collaboration within the CPC and the broader University of Sydney community that involves novel statistical models and machine learning algorithms to better analyse large genomic data sets, such as the UK Biobank and other modern genomic data sets of similar scale. 
- undertake teaching duties where required 
- undertake administrative duties to manage the Data Science Hub. 

About you 

The University values courage and creativity; openness and engagement; inclusion and diversity; and respect and integrity. As such, we see the importance of recruiting talent aligned to these values and are looking for a Senior Research Fellow / Data Science Hub Statistician who has: 

- experience as academic track researcher or leading a research program 
- track record of initiating and leading major collaborative projects 
- strong background in the development of novel and applied statistical approaches to analyse large-scale datasets 
- experience in implementing, and scaling these methods using robust programming tools and practices for the University and the wider community 
- demonstratable track record of expertise in one of the following areas: large biobank data management and analysis, health data management and analysis from large population databases and cohorts, complex systems modelling, or multi-omics and mass spectrometry data and analysis. 

Job website:  https://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Camperdown-Campus/Data-Science-Hub-Statistician_0127160

Contact name: Amber Colhoun

Contact email: data-science.admin@sydney.edu.au

Bioinformatics Research Officer @ Computational Sciences Initiative, Doherty Institute, The University of Melbourne

Employer : Computational Sciences Initiative, Doherty Institute, The University of Melbourne

Closing date:   20/12/2024


Brief position description:
  

The Computational Sciences Initiative (CSI) at the Doherty Institute is recruiting a Bioinformatics Research Officer. This role will conduct bioinformatics analyses on projects in the areas of immunology and infectious diseases for a new Bonn-Cumming Program at the Institute, which seeks to develop novel innate immunity therapeutics. 

Responsibilities include:
- Using best-practice pipelines for analysis of multi-omic data generated by collaborators. This includes: integration of high-dimensional data sets, best-practice programming practices, establishment of code-review activities, and appropriate version control.
- Assisting the development of a strong program of collaborative research in bioinformatics with Bonn-Cumming researchers in the Doherty Institute.
- Developing new methods and software packages for analysis of different mutli-omic sequence-based or other high dimensional analyte data where appropriate.
- Assisting other researchers in carrying out experiments to work as a team and further the department’s research output.

Please see the below link for more information.

Please contact Jan Schroeder with further queries: jan.schroeder@unimelb.edu.au

Job website:  http://jobs.unimelb.edu.au/caw/en/job/918956/research-officer-bioinformatician

Contact name: Jan Schroeder

Contact email: jan.schroeder@unimelb.edu.au

Director, Bioinformatics & AI @ CSL

Employer : CSL

Closing date:   17/12/2024


Brief position description:
  

Your Role 

In the role of Director, Bioinformatics & AI you will lead a team focused on the method development and application of computational approaches for addressing scientific questions in pre-clinical research and translational medicine; focusing on genetics, omics, imaging, biomedical literature, and RWD data modalities. As a member of the biomedical Data Science Leadership Team, you will help shape the direction of the global data science team and its role within the broader CSL R&D ecosystem.

Your Responsibilities

Reporting to the Senior Director, Global Head of Data Science you will:

Be accountable for activities focused on development and application of computational methods for enabling research biology and translational medicine activities
Support and implement a robust and inclusive recruitment and talent development strategy to attract talent, and provide scientific and career development mentorship
Work across Global Research organisation with therapeutic area leads, project managers and scientific coordinators to enable seamless and impactful integration of computational scientists across the project portfolio landscape
Drive partnerships between your team and Data Management and Engineering and Biostatistics teams.
Work to develop overall competency of direct reports and data literacy amongst scientists at CSL, encouraging learning and development opportunities
Maintain and build CSL’s research profile within industry contacts and networks
Ensure your team is globally visible across CSL, including publication in high-impact scientific journals and participation in international conferences
Actively foster an inclusive, ethical, and diverse team culture

Your Experience

A PhD and 8+ years of experience in a relevant scientific discipline and drug development
Recognition as a world-leading scientist in your area of work, excellent publication record and participation in international meetings and conferences. Membership of relevant scientific bodies.
Demonstrated leadership skills, and a track record of developing early & mid-career scientists
Experience of working in an interdisciplinary research environment and a track record of partnering and building successful relationships within and between organisations/institutes
Excellent oral and written communication skills
Experience in managing large and complex projects and teams, involving multiple stakeholders and achieving results in a timely and resource efficient manner 

Job website:  http://lnkd.in/gX3ksQkQ

Contact name: Milica Ng

Contact email: milica.ng@csl.com.au

Computational Data Scientist @ Melanoma Institute Australia

Employer : Melanoma Institute Australia

Closing date:   11/12/2024


Brief position description:
  

Melanoma Institute Australia (MIA) is an independent, non-profit organisation with its head office located near North Sydney. MIA is affiliated with the University of Sydney and is world’s largest treatment and research centre with a single focus on melanoma, and our mission is to reach zero deaths from melanoma this decade.

The Personalised Immunotherapy Program (PIP) is a 5-year program which applies machine learning- based models to identify patients with cancer that is likely to be unresponsive to anti-cancer immunotherapies. PIP aims to ensure each patient’s cancer is screened for genetic, transcriptomic, and immune profiles to identify patients unlikely to benefit from standard therapies. The team has a wealth of multi-omics datasets and is currently deploying predictive models into oncology clinicals in real-time.

The PIP team is seeking a full time experienced Computational Data Scientist with a strong analytical background to leverage the vast resources available to monitor and improve the accuracy of melanoma diagnosis, prognosis, and suitability of anti-cancer therapies. The position entails deploying machine learning models to identify patient responses to therapies using clinical and multi-omics data sets and overseeing the long-term accuracy of the predictive models. The candidate will also build on these models with new approaches and additional information from novel technologies to improve patient selection for systemic therapies.

The data scientist will be responsible for the implementation of predictive models into a biomarker program within oncology clinics. The role will work alongside multiple clinical and research teams to interrogate multi-omics datasets, imaging data and other resources available at MIA. This role will require the candidate to have excellent computational skills, preferred experience in the cancer setting, and a passion to improve cancer patient outcomes.

The successful candidate will be part of the PIP team that resides within the Translational Research Laboratory of the Melanoma Institute Australia, based at The University of Sydney Camperdown campus. This is a fixed term position until December 2026 with view to a permanent role upon completion of fixed term contract. Applications that do not address the selection criteria will not be processed.


Key Selection Criteria

To be successful in this role you will have:

PhD in data science, computational biology or related field
Demonstrated skills in computer languages (eg –Python, R)
Experience in processing and analysing multi-omics and/or imaging datasets.
Experience in deploying machine learning models
Scientific track record in developing machine learning models
Experience in the clinical integration of multi-omics datasets
Knowledge in deploying predictive models in the clinical setting
Excellent project management skills with the ability to multitask.
Preferred working knowledge of cancer biology and/or immunology
Preferred interest in spatial biology and emerging technologies.

Job website:  https://www.seek.com.au/Melanoma-Institute-Australia-jobs?jobId=80431713&type=standout

Contact name: James Wilmott

Contact email:  james.wilmott@sydney.edu.au

Computational Data Scientist @ Melanoma Institute Australia

Employer : Melanoma Institute Australia

Closing date:   24/12/2024


Brief position description:
  

The Personalised Immunotherapy Program (PIP) is a 5-year program which applies machine learning- based models to identify patients with cancer that is likely to be unresponsive to anti-cancer immunotherapies. PIP aims to ensure each patient’s cancer is screened for genetic, transcriptomic, and immune profiles to identify patients unlikely to benefit from standard therapies. The team has a wealth of multi-omics datasets and is currently deploying predictive models into oncology clinicals in real-time.

The PIP team is seeking a full time experienced Computational Data Scientist with a strong analytical background to leverage the vast resources available to monitor and improve the accuracy of melanoma diagnosis, prognosis, and suitability of anti-cancer therapies. The position entails deploying machine learning models to identify patient responses to therapies using clinical and multi-omics data sets and overseeing the long-term accuracy of the predictive models. The candidate will also build on these models with new approaches and additional information from novel technologies to improve patient selection for systemic therapies.

The data scientist will be responsible for the implementation of predictive models into a biomarker program within oncology clinics. The role will work alongside multiple clinical and research teams to interrogate multi-omics datasets, imaging data and other resources available at MIA. This role will require the candidate to have excellent computational skills, preferred experience in the cancer setting, and a passion to improve cancer patient outcomes.

The successful candidate will be part of the PIP team that resides within the Translational Research Laboratory of the Melanoma Institute Australia, based at The University of Sydney Camperdown campus. 

Key Selection Criteria
To be successful in this role you will have:
- PhD in data science, computational biology or related field
- Demonstrated skills in computer languages (eg –Python, R)
- Experience in processing and analysing multi-omics and/or imaging datasets.
- Experience in deploying machine learning models
- Scientific track record in developing machine learning models
- Experience in the clinical integration of multi-omics datasets
- Knowledge in deploying predictive models in the clinical setting
- Excellent project management skills with the ability to multitask.
- Preferred working knowledge of cancer biology and/or immunology
- Preferred interest in spatial biology and emerging technologies.

This is a fixed term position until December 2026 with view to a permanent role upon completion of fixed term contract.

Job website:   http://www.seek.com.au/job/80431713?tracking=SHR-WEB-SharedJob-anz-1

Contact name: Ann Michelle Arrabaca

Contact email: Careers@melanoma.org.au

Senior Bioinformatician (Australian BioCommons) @ Sydney Informatics Hub, University of Sydney

Employer : Sydney Informatics Hub, University of Sydney

Closing date:   4/12/2024


Brief position description:
  

The Sydney Informatics Hub (SIH) is looking for a senior bioinformatician to join our growing partnership with Australian BioCommons. We’re working with Australian BioCommons to empower life scientists with digital infrastructure, providing expertise in bioinformatics, software engineering, and training. We collaborate with University of Sydney researchers and our external partners to develop open-source tools and services for national priorities like precision medicine, environmental conservation, and agriculture. 

Your key responsibilities will be to:
• collaborate within cross-functional teams across SIH, Uni of Sydney, national supercomputing facilities, and Australian BioCommons
• apply your expertise in high-performance computing, cloud computing, and bioinformatics to design and implement impactful solutions
• lead bioinformatics analyses, data engineering, and software projects
• develop and deliver training events for the National Bioinformatics Training Cooperative
• strengthen our team capabilities in software development and translational bioinformatics
• cultivate an engineering and entrepreneurial ethos to support bioinformatics initiatives throughout Uni of Sydney and nationally

Job website:  http://usyd.wd3.myworkdayjobs.com/USYD_EXTERNAL_CAREER_SITE/job/Newtown/Senior-Bioinformatician_0126133-2

Contact name: Georgie Samaha

Contact email: georgina.samaha@sydney.edu.au

Genomics Software Developer (Data Scientist) or Genomics Data Analyst (Information Sciences Professional) @ Dashnow Lab, University of Colorado Anschutz Medical Campus

Employer : Dashnow Lab, University of Colorado Anschutz Medical Campus

Closing date:   13/11/2024  (midnight US Mountain time)


Brief position description:
  

Join a department with views of the Rocky Mountains! Relocation and visa support are available.

The Dashnow Lab in the Department of Biomedical Informatics at the University of Colorado Anschutz Medical Campus is seeking a Data Scientist or Information Sciences Professional with a background in computer science, data science, human genomics, bioinformatics, computational biology, statistics, or related fields. This role can also be described as a scientific software developer, staff scientist, data analyst or computational research assistant. Individuals from diverse or non-traditional backgrounds are strongly encouraged to apply, including those transitioning fields.

The Dashnow Lab develops computational genomics methods to understand the genetic underpinnings of rare diseases and increase diagnoses. We have particular expertise in difficult-to-genotype repetitive regions such as tandem repeats. We develop and apply these methods at scale to current and emerging DNA sequencing technologies. Our research directly impacts individuals with rare diseases and their families, giving them answers and hope for treatment after a long diagnostic odyssey. The lab has strong national and international collaborations, including with large, rare disease and population consortiums and with industry. Current project funding supports new approaches for diagnosis and gene discovery for short tandem repeat diseases, computational methods development for both short and long-read sequencing technologies, and population genetics.

Two positions are posted. Please apply to the position that best matches your qualifications and experience.
Genomics Software Developer (Data Scientist) https://cu.taleo.net/careersection/2/jobdetail.ftl?job=35396&lang=en
Genomics Data Analyst (Information Sciences Professional) https://cu.taleo.net/careersection/2/jobdetail.ftl?job=35393&lang=en

Job website: https://smex-ctp.trendmicro.com:443/wis/clicktime/v1/query?url=http%3a%2f%2fwww.dashnowlab.org&umid=c88e1401-02dc-4bee-82fd-d742c938311b&auth=6ee66d642a212b82964c9073f0dd934b55317413-83cf852d02e3a15b164ff0742509c6d21eddca1e

Contact name: Harriet Dashnow

Contact email: harriet.dashnow@cuanschutz.edu

Clinical Microbiologist (Pathogen Genomics) @ Microba

Employer : Microba

Closing date:   31/12/2024


Brief position description:
  

Position Title: Clinical Microbiologist (Pathogen Genomics)
Location: Brisbane, Queensland, Australia
Status: Permanent Full Time

Join Microba’s Bioinformatics team and lead innovations in infectious disease diagnostics! This role focuses on driving metagenomic-based infectious disease diagnostic testing for healthcare partners, collaborating with cross-functional teams to deliver novel and impactful health outcomes to patients.

Key Responsibilities
Lead research and integration of pathogen and AMR targets into our ISO15189 accredited tests
Oversee test delivery, support test accuracy, and support report clinical and scientific interpretation
Engage with stakeholders to advance test adoption and communicate performance insights

Skills & Experience
PhD in Clinical Microbial Genomics or similar, with 4+ years of post-doctoral/clinical research
Strong knowledge in microbial pathogenicity, antimicrobial resistance, and bioinformatics..

Job website: https://smex-ctp.trendmicro.com:443/wis/clicktime/v1/query?url=https%3a%2f%2fjobs.swagapp.com%2fjobs%2fmicroba%2dclinical%2dmicrobiologist%2dpathogen%2dgenomics&umid=ee045f3e-bc07-4464-966d-f706f949ec11&auth=6ee66d642a212b82964c9073f0dd934b55317413-551d9ed92b2ce0070729b51db714d7d573331733

Contact name:   Jenni Levingston

Contact email: peopleandculture@microba.com

Associate Research Fellow / Research Fellow, Bioinformatician @ Deakin University

Employer : Deakin University

Closing date:   27/10/2024


Brief position description:
  The Institute for Mental and Physical Health and Clinical Translation (IMPACT) in Deakin’s School of Medicine is seeking a Level A or B Research Fellow to initiate, design, and conduct productive, high-quality research, scholarship and creative activities to generate high-impact outputs.

Job website:  https://careers.deakin.edu.au/en/job/563960/associate-research-fellow-research-fellow-bioinformatician

Contact name:   Jess Fulmer

Contact email: j.fulmer@deakin.edu.au