Job Information
- Organisation/Company: George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș
Offer Description
UMFST Târgu Mureș, Romania, invites applications from doctoral students for a part-time Bioinformatics Research Assistant position within the Core Bioinformatics group of the NeuRoX project. Reporting to Prof Irina Mohorianu, the successful candidate will analyse single-cell and spatial -omics datasets, across modalities (epigenetics, transcriptomics, proteomics, metabolomics) to infer robust, reproducible gene regulatory networks and investigate their dynamics and causality in the context of neurodegenerative pathologies.
The position is for up to 60 hours per month. Tasks and deadlines will be agreed with the line manager to match this commitment and the candidate’s doctoral study schedule. The fixed-term appointment will run from 15th November 2026 to 31st December 2030.
Role and Responsibilities
Working under the supervision of Prof Irina Mohorianu, you will contribute to the analysis of single-cell and spatial datasets in the context of neurodegenerative diseases and contribute to the NeuRoX project. The scientific aim is to infer gene regulatory networks reliably and investigate how regulatory interactions change and contribute to neurodegenerative pathologies. Your responsibilities will include:
- Organising single-cell and spatial datasets and relevant metadata, checking completeness and documenting data provenance and processing decisions.
- Performing quality control, preprocessing, cell type or state annotation, and exploratory analysis, accounting for batch effects and spatial structure where relevant.
- Implementing, comparing and optimising gene regulatory network inference methods in R and/or Python, using data science, machine learning and AI approaches where appropriate; assessing robustness, scalability and computational efficiency.
- Contributing to the development, testing and documentation of reproducible workflows, including version control and clear records of software versions and parameters.
- Interpreting regulatory modules, candidate regulators and network changes in neurodegenerative pathologies, and communicating findings and limitations through figures, tables and reports.
- Analysing network dynamics across cell states, disease conditions and spatial contexts; investigating causal hypotheses using suitable methods and available evidence, and distinguishing association from supported causal inference.
- Participating in relevant group and project meetings and contributing to manuscripts or presentations where appropriate to the work undertaken.
- Following institutional requirements for research integrity, secure data handling, confidentiality and responsible use of shared computing resources.
Work priorities will be reviewed regularly. The role is intended to provide a manageable contribution to the project alongside doctoral study, with all assigned duties, including meetings and documentation, included in up to 60 monthly hours.
Where to apply
E-mail: iim22@cam.ac.uk
Requirements
- Research Field: Computer science
- Education Level: PhD or equivalent
Skills/Qualifications
Desirable Experience
Applicants are not expected to have experience in every area below. Relevant training and willingness to learn will also be considered.
- Experience analysing single-cell or spatial transcriptomic datasets, including quality control, normalisation, annotation and integration; an understanding of sequencing-based quantification, even at bulk level, is essential. Solid understanding of transcriptomics is a must; knowledge of other modalities is a bonus.
- Familiarity with Linux, command line tools, Git and reproducible analysis environments.
- Experience with workflow systems such as Nextflow or Snakemake, or shared high-performance computing resources; demonstrable knowledge of building R/ Python packages.
- Experience with gene regulatory network inference, network analysis, trajectory analysis, dynamical modelling or causal inference.
- An interest in neurodegeneration and in interpreting regulatory mechanisms across cell types, disease states and tissue contexts.
Specific Requirements
- Current registration for a doctoral degree in bioinformatics, computational biology, computer science, statistics, or a closely related discipline.
- A background in computer science, demonstrated through a relevant degree or equivalent training, with a MSc degree in Bioinformatics or Artificial Intelligence and/or Optimisation, or equivalent qualification supporting admission to doctoral study.
- Practical programming experience in R and/or Python; experience with C/C++ optimisation is desirable; documented ability to write clear analysis code and work with structured research data.
- A good command of data science, machine learning and AI approaches, including statistical foundations, model evaluation and the interpretation of computational results.
- Ability to organise tasks, document work accurately, meet agreed deadlines and seek guidance when needed.
- Ability to work collaboratively across disciplines and communicate clearly in spoken and written English.
- Good knowledge of optimisation of computational frameworks and methods, including algorithm design, parameter tuning, scalability and computational efficiency.
- Languages: ROMANIAN — Level: Mother Tongue
- Languages: ENGLISH — Level: Good
- Research Field: Computer science
Additional Information
Benefits
- Practical experience in collaborative bioinformatics research within NeuRoX.
- Supervision and feedback from the Core Bioinformatics group, with opportunities to strengthen computational, analytical and scientific communication skills.
- Access to the software, computing resources and training needed for the assigned tasks.
- Opportunities to contribute to scientific outputs, with contributions recognised according to applicable authorship and acknowledgement practices.
- The position is based at UMFST Târgu Mureș, Romania, with hybrid or remote arrangements. The distribution of the 60 monthly hours will be agreed with the line manager, taking into account project needs, team availability and doctoral commitments.
- Employment terms, leave and any staff benefits will be specified in the contract in accordance with the employing institution’s policies.
Eligibility criteria
- Current registration for a doctoral degree in bioinformatics, computational biology, computer science, statistics, or a closely related discipline.
- A background in computer science, demonstrated through a relevant degree or equivalent training, with a MSc degree in Bioinformatics or Artificial Intelligence and/or Optimisation, or equivalent qualification supporting admission to doctoral study.
- Practical programming experience in R and/or Python; experience with C/C++ optimisation is desirable; documented ability to write clear analysis code and work with structured research data.
- A good command of data science, machine learning and AI approaches, including statistical foundations, model evaluation and the interpretation of computational results.
- Ability to organise tasks, document work accurately, meet agreed deadlines and seek guidance when needed.
- Ability to work collaboratively across disciplines and communicate clearly in spoken and written English.
- Good knowledge of optimisation of computational frameworks and methods, including algorithm design, parameter tuning, scalability and computational efficiency.
Additional comments
Submit your application through email at iim22@cam.ac.uk, roxcarare@gmail.com, proiecte@umfst.ro by 21/10/2026 @23:59 GMT+2.
Please include:
- A motivation letter of no more than one page explaining your relevant experience, interest in NeuRoX and availability for 60 hours per month.
- A CV outlining education, doctoral research, programming skills and relevant analysis experience.
- Evidence of current doctoral registration and relevant degree qualifications.
- Contact details for one or two academic or professional referees.
- Optional examples of analysis code, a repository (e.g. a GitHub repository), a report or a publication demonstrating relevant skills. Do not submit confidential data or code.
Selection will consider relevant skills, motivation, ability to collaborate and fit with the agreed project tasks. Shortlisted candidates will be invited to an interview.
Questions
Scientific enquiries: Prof Irina Mohorianu, line manager, iim22@cam.ac.uk
Work Location(s)
- Number of offers available: 2
- Company/Institute: George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș
- Country: Romania
- State/Province: MURES
- City: TARGU MURES
- Postal Code: 540139
- Street: Strada Gheorghe Marinescu nr 38
Contact
- State/Province: Mures
- City: Targu Mures
- Website: https://www.umfst.ro/home.html
- Street: Gheorghe Marinescu, 38
- Postal Code: 540142