Question 1

Bioinformatician Position in Multi-Omics Data Analysis -Heidelberg, Germany

Accepted Answer

Heidelberg University is inviting applications for a full-time Bioinformatician (f/m/d) position in Multi-Omics Data Analysis and Integration (COMBI-OMICS), starting 1 January 2027.

The position is aimed at a bioinformatics scientist interested in developing reproducible computational workflows, multi-omics integration, and data-driven biological interpretation at the interface of computational biology, experimental core facilities, and biomedical research.

About the Project

COMBI-OMICS (Core-Facility Bioinformatics Integration for Multi-Omics Analyses) is a collaborative initiative involving multiple Heidelberg research core facilities, including metabolomics, proteomics, transcriptomics, spatial profiling, and deep sequencing.

The successful candidate will help build reusable bioinformatics workflows and provide computational support for integrated multi-omics research projects across the Heidelberg life science campus.

Main Responsibilities

The researcher will work on:

Developing reproducible workflows using Nextflow/nf-core

Analysing metabolomics, proteomics/phosphoproteomics, transcriptomics and spatial profiling data

Developing tools for quality control, preprocessing and statistical analysis

Performing multi-omics integration, pathway and network analysis

Creating automated reports and data visualizations

Supporting researchers with study design, analysis and biological interpretation

Contributing to publications, SOPs, training resources and funding applications

Requirements

Applicants should have:

A PhD in Bioinformatics, Computational Biology, Systems Biology, Biostatistics, Data Science or a related field

Strong programming skills in R and/or Python

Experience with reproducible computational workflows and software development practices

Experience with Nextflow/nf-core or comparable workflow systems such as Snakemake, WDL or CWL

Practical experience with at least two types of high-throughput omics data

Understanding of experimental design, batch effects and biological variation

Strong communication and collaboration skills

Excellent English; German is an advantage

Experience with Docker/Apptainer, HPC or cloud computing, multi-omics integration, pathway/network analysis, and open-source software will be an advantage.

Position Details

📍 Location: Heidelberg, Germany🏛️ Institution: Heidelberg University💼 Position: Bioinformatician (f/m/d)🔬 Area: Multi-Omics Data Analysis & Integration🗓️ Start Date: 1 January 2027⏱️ Working Hours: Full-time, 39.5 hours/week💰 Salary: TV-L E13📅 Contract: 2 years (1 January 2027 – 31 December 2028)📌 Application Deadline: 18 September 2026

Continuation beyond the initial contract may be possible depending on project development and follow-up funding.

How to Apply

Applicants should submit their application as one single PDF containing:

CV

Motivation letter

Certificates

Publication list

Contact details of referees

The application should clearly mention your experience with omics data types, statistical/integration methods, programming languages, workflow tools and relevant software. A GitHub profile can also be provided if available.

📧 Application: cos-sekretariat360@listserv.uni-heidelberg.de

Contact: Dr. Gernot Poschet — gernot.poschet@cos.uni-heidelberg.de

Official Information

For complete details and application information, applicants should refer to the official Heidelberg University job advertisement and job-market page.

Application deadline: 18 September 2026

Question 2

PhD Position in Immunometabolism – Ulm, Germany

Accepted Answer

A PhD position in Immunometabolism is available in the Fischer-Posovszky Lab, Department of Pediatrics and Adolescent Medicine at Ulm University Medical Center, Germany.

Research Project

Beyond Fat Storage: Uncovering the Immune Functions of Adipocytes

Adipocytes are increasingly understood as active endocrine and immune-regulatory cells rather than simply energy-storage cells. This PhD project will investigate how adipocytes detect pathogens, interact with immune cells, and contribute to antimicrobial host defense.

The successful candidate will study adipocyte–immune cell communication and host–pathogen interactions using human adipocyte models and modern molecular and cellular approaches.

Research Methods

The project will combine:

CRISPR/Cas9 gene editing

Cell and molecular biology

Immunological assays

Flow cytometry

Single-cell analysis

Functional assays

Human adipocyte models

The research offers an opportunity to work at the intersection of immunology, cell biology, metabolism, and host–pathogen biology.

Candidate Profile

Applicants should have an excellent Master&#8217;s degree in Biology, Molecular Medicine, Biochemistry, Biotechnology, Immunology, or a related field.

Previous experience in cell biology, molecular biology, or immunology is advantageous. The position is suited for candidates who are enthusiastic about experimental research, comfortable working in interdisciplinary teams, and have good English communication skills.

Position Details

📍 Location: Ulm, Germany🔬 Research Area: Immunometabolism & Adipocyte Immunity🎓 Position: PhD Student (m/f/d)🗓️ Expected Start: November 2026💰 Salary: TV-L E13, 65% (depending on qualification and experience)⏳ Contract: Limited🕐 Employment: Part-time📅 Application Deadline: 21 September 2026

What the University Offers

Membership in the International Graduate School in Molecular Medicine Ulm (IGradU)

State-of-the-art research facilities and core technologies

An international and collaborative research environment

Opportunities to attend international conferences

Opportunities for scientific publications

How to Apply

Applicants should submit one merged PDF file containing:

Letter of motivation

CV

Degree certificates

Academic transcripts/grade sheets for B.Sc., M.Sc., and other degrees

Applications should be sent to:

📧 Prof. Dr. Pamela Fischer-Posovszkypamela.fischer@uniklinik-ulm.de

For further information or questions regarding the position, candidates can contact the supervisor directly by email.

Application deadline: 21 September 2026

🔗 Official Job Advertisement: View the official PhD position at Ulm University Medical Center

Question 3

Can you explain CAR-T?

Accepted Answer

Chimeric Antigen Receptor T-cell therapy, commonly referred to as CAR-T therapy or CAR-T cell therapy, is a groundbreaking immunotherapy that has shown remarkable success in the treatment of certain types of cancer, particularly blood cancers like leukemia and lymphoma. CAR-T therapy involves genetically modifying a patient&#8217;s own T cells (a type of immune cell) to target and destroy cancer cells.

Here&#8217;s an overview of the key aspects of CAR-T therapy:

Collection of T Cells: The process begins by extracting T cells from the patient&#8217;s blood. This is typically done through a process called leukapheresis, in which the patient&#8217;s blood is passed through a machine that separates the T cells and returns the remaining blood components.

Genetic Modification: The isolated T cells are then genetically engineered to express a Chimeric Antigen Receptor (CAR) on their surface. The CAR is a synthetic protein that combines an antigen-binding domain (usually derived from an antibody) and intracellular signaling domains. The antigen-binding domain allows the CAR-T cells to recognize a specific protein or antigen commonly found on the surface of cancer cells.

Expansion and Activation: The modified T cells are cultured and expanded in the laboratory to create a large population of CAR-T cells. During this process, the T cells are also activated to become more potent in their cancer-fighting capabilities.

Infusion: Once a sufficient number of CAR-T cells are produced, they are infused back into the patient&#8217;s bloodstream through a vein, similar to a blood transfusion.

Targeting Cancer Cells: The infused CAR-T cells circulate in the patient&#8217;s body and, when they encounter cancer cells expressing the target antigen, they bind to them through the CAR. This binding triggers the CAR-T cells to initiate a series of immune responses, including the destruction of the cancer cells.

Proliferation and Persistence: CAR-T cells can proliferate within the patient&#8217;s body, leading to a potentially long-lasting immune response against cancer. This is a significant advantage, as it allows for ongoing surveillance and targeted elimination of cancer cells.

Side Effects: CAR-T therapy can lead to side effects, which can range from mild flu-like symptoms to more severe cytokine release syndrome (CRS) and neurological toxicity. These side effects are managed by healthcare providers, and treatments, including medications, are available to address them.

Monitoring and Follow-Up: Patients who receive CAR-T therapy require close monitoring to assess its effectiveness and manage any potential side effects. Regular follow-up visits are essential to evaluate the patient&#8217;s condition.

CAR-T therapy has shown remarkable success, particularly in treating certain types of leukemia and lymphoma, including acute lymphoblastic leukemia (ALL) and diffuse large B-cell lymphoma (DLBCL). It has revolutionized the field of cancer immunotherapy and holds promise for further applications in treating other types of cancer.

However, it&#8217;s important to note that CAR-T therapy is a highly specialized and complex treatment that is not suitable for all cancer types or all patients. It is typically reserved for cases where other treatments have been unsuccessful, and the benefits outweigh the potential risks. Clinical trials and ongoing research are continually expanding the understanding and potential applications of CAR-T therapy in the field of oncology.

Question 4

Neuroscience and Regeneration Biology

Accepted Answer

Neuroscience and regeneration biology are two interconnected fields of study that focus on understanding the nervous system and its ability to repair and regenerate after injury or damage. Let&#8217;s explore these fields in more detail:

Neuroscience:

Neuroscience is the scientific study of the nervous system, which includes the brain, spinal cord, and peripheral nerves. It seeks to understand how the nervous system functions, how it controls various physiological and cognitive processes, and how it can be affected by diseases and injuries.

Neuroscientists use various techniques, including neuroimaging, electrophysiology, and molecular biology, to investigate the structure and function of neurons (nerve cells) and their interactions in complex neural networks.

Key areas of neuroscience research include neuroanatomy, neurophysiology, neurochemistry, and neuropharmacology.

Neuroscientists also study brain development, neuroplasticity (the brain&#8217;s ability to adapt and change), and the neural basis of behavior, cognition, and emotions.

Regeneration Biology:

Regeneration biology is a branch of biology that focuses on the study of regenerative processes in living organisms, including the ability of tissues and organs to repair and replace damaged or lost cells.

While many animals possess varying degrees of regenerative abilities, some organisms, such as salamanders and starfish, are known for their remarkable regenerative capabilities. For example, certain species of salamanders can regenerate entire limbs, including bones, muscles, and nerves.

Regeneration biology seeks to understand the molecular and cellular mechanisms underlying regeneration, including the role of stem cells and signaling pathways.

Researchers in this field aim to apply their findings to medical science and regenerative medicine, with the goal of developing therapies to promote tissue regeneration and repair in humans.

Intersections between Neuroscience and Regeneration Biology:

In the context of neuroscience, regeneration biology plays a crucial role in understanding the potential for nerve tissue repair and recovery after injuries to the nervous system.

Researchers investigate how neurons and glial cells (supporting cells in the nervous system) respond to injuries and whether interventions can enhance their regenerative capacity.

Stem cell therapy is an area where neuroscience and regeneration biology intersect. Scientists explore the use of stem cells to replace damaged or lost neurons and restore neural function in conditions like spinal cord injuries or neurodegenerative diseases.

Understanding regenerative processes in the nervous system can also lead to insights into treatments for conditions like stroke, traumatic brain injury, and neurodegenerative disorders.

In summary, neuroscience and regeneration biology are interdisciplinary fields that collaborate to uncover the mysteries of the nervous system&#8217;s functioning and its potential for repair and regeneration. These fields hold promise for improving our understanding of neurological disorders and developing innovative therapies for nervous system injuries and diseases.

Question 5

What is the linear and discontinuous B cell epitope prediction, and how to perform in silico?

Accepted Answer

Linear and discontinuous B-cell epitope prediction are two different approaches used in immunoinformatics to identify regions of a protein that are likely to be recognized by antibodies (B-cell epitopes). Here&#8217;s an overview of each and how to perform them in silico:

1. Linear B-Cell Epitope Prediction:

Linear epitopes are continuous sequences of amino acids within a protein that are recognized by antibodies. These epitopes are typically found on the protein&#8217;s surface.

In silico prediction of linear B-cell epitopes involves using computational tools and algorithms to analyze the primary amino acid sequence of a protein to identify regions with the potential to bind to antibodies.

How to Perform Linear B-Cell Epitope Prediction in Silico:

a. Choose a Prediction Tool: There are several online tools and software packages available for linear B-cell epitope prediction, such as:

BepiPred: This tool predicts linear B-cell epitopes using a combination of methods, including hidden Markov models (HMMs) and propensity scales.

ABCpred: ABCpred is a machine learning-based method that predicts B-cell epitopes based on input protein sequences.

b. Input Sequence: Provide the amino acid sequence of the protein of interest to the chosen prediction tool.

c. Run the Prediction: Submit the sequence, and the tool will analyze it based on its algorithms to identify regions likely to be linear B-cell epitopes.

d. Interpret the Results: The tool will provide predictions in the form of scores or probability values for different regions of the protein. High-scoring regions are more likely to be linear epitopes.

e. Validation: Experimental validation (e.g., enzyme-linked immunosorbent assay or ELISA) is often necessary to confirm the predicted linear epitopes.

2. Discontinuous (Conformational) B-Cell Epitope Prediction:

Discontinuous epitopes, also known as conformational epitopes, are formed by amino acids that are not adjacent in the primary sequence but come together in the three-dimensional structure of a protein. These epitopes are often dependent on the protein&#8217;s folded conformation.

In silico prediction of discontinuous B-cell epitopes involves analyzing the protein&#8217;s three-dimensional structure or using computational modeling to identify regions where amino acids are brought into proximity in the folded protein.

How to Perform Discontinuous B-Cell Epitope Prediction in Silico:

a. Obtain the Protein Structure: If available, obtain the three-dimensional structure of the protein using techniques like X-ray crystallography or NMR spectroscopy. Alternatively, use protein structure prediction tools.

b. Choose a Prediction Tool: Several tools and algorithms are available for discontinuous epitope prediction, including:

DiscoTope: DiscoTope uses a neural network-based approach to predict discontinuous B-cell epitopes based on protein structure.

Ellipro: Ellipro analyzes protein structures and calculates protrusion index to predict potential epitopes.

c. Input Structure: Provide the protein structure in a compatible format (e.g., PDB format) to the chosen prediction tool.

d. Run the Prediction: The tool will analyze the protein structure and predict regions where discontinuous B-cell epitopes are likely to be located.

e. Interpret the Results: The tool will provide scores or probability values for different regions of the protein structure, indicating the likelihood of epitope presence.

f. Validation: Experimental methods like epitope mapping assays (e.g., site-directed mutagenesis and antibody binding assays) are used to validate predicted discontinuous epitopes.

Both linear and discontinuous B-cell epitope prediction methods have their advantages and limitations, and combining them can provide a more comprehensive view of potential epitopes within a protein. The choice of method depends on the availability of protein structure data and the specific goals of the epitope prediction study.

Question 6

What are the potential applications of mRNA technology?

Accepted Answer

mRNA (messenger RNA) technology has demonstrated immense potential beyond its use in COVID-19 vaccines. Its versatility and ability to instruct cells to produce specific proteins make it a promising platform for a wide range of applications in medicine and biotechnology. Some potential applications of mRNA technology include:

Vaccines: mRNA vaccines have already been successfully developed for COVID-19. This platform can be rapidly adapted to address other infectious diseases, including influenza, Zika virus, and HIV, as well as emerging pathogens. mRNA vaccines may also be used for personalized cancer vaccines.

Cancer Immunotherapy: mRNA technology can be applied to develop personalized cancer immunotherapies. By encoding tumor-specific antigens in mRNA, it&#8217;s possible to stimulate the patient&#8217;s immune system to recognize and attack cancer cells while sparing healthy tissue.

Protein Replacement Therapies: For genetic disorders caused by mutations that result in nonfunctional or deficient proteins, mRNA can be used to deliver the correct genetic instructions to produce functional proteins. This approach is being explored for diseases like cystic fibrosis and certain types of muscular dystrophy.

Therapeutic Antibodies: mRNA can be used to instruct cells to produce therapeutic antibodies, which could provide a more rapid and scalable approach to antibody production for treating various diseases, including infectious diseases and cancer.

Regenerative Medicine: mRNA technology can play a role in regenerative medicine by guiding the differentiation of stem cells into specific cell types for tissue repair and replacement. This could be valuable for treating conditions such as Parkinson&#8217;s disease or spinal cord injuries.

Metabolic Disorders: mRNA therapies may be used to treat metabolic disorders like phenylketonuria (PKU) by encoding enzymes that are missing or dysfunctional in affected individuals.

Rare Diseases: For rare genetic diseases with limited treatment options, mRNA technology offers a potential avenue for developing targeted therapies.

Immune Modulation: mRNA can be designed to modulate the immune system, which could be useful for treating autoimmune diseases or enhancing the immune response against certain infections.

Enzyme Replacement: Similar to protein replacement therapies, mRNA can be used to replace missing or defective enzymes in conditions like lysosomal storage diseases.

Neurodegenerative Diseases: Researchers are exploring the use of mRNA technology to develop therapies for neurodegenerative diseases like Alzheimer&#8217;s and Huntington&#8217;s disease.

Antiviral Therapies: mRNA-based approaches can be explored for the development of antiviral treatments against various viruses, not just SARS-CoV-2.

Gene Editing and CRISPR Delivery: mRNA can be used as a carrier to deliver gene-editing tools like CRISPR-Cas9 to specific cells or tissues for precise gene editing.

Diagnostics: mRNA-based diagnostic tests can be developed to detect specific genetic markers or pathogens, offering rapid and sensitive diagnostic tools.

Drug Discovery: mRNA technology can be used in drug discovery pipelines for target validation and screening potential drug candidates.

Biomanufacturing: mRNA technology can improve the production of therapeutic proteins, enzymes, and antibodies in biomanufacturing processes.

It&#8217;s important to note that while mRNA technology holds tremendous promise, there are still challenges to overcome, including optimizing delivery methods, addressing potential immune responses, ensuring long-term safety, and developing regulatory frameworks. Ongoing research and development efforts in this field are likely to lead to new breakthroughs and applications in the coming years.

Question 7

Bioinformatician Position in Multi-Omics Data Analysis -Heidelberg, Germany

Accepted Answer

Heidelberg University is inviting applications for a full-time Bioinformatician (f/m/d) position in Multi-Omics Data Analysis and Integration (COMBI-OMICS), starting 1 January 2027.

The position is aimed at a bioinformatics scientist interested in developing reproducible computational workflows, multi-omics integration, and data-driven biological interpretation at the interface of computational biology, experimental core facilities, and biomedical research.

About the Project

COMBI-OMICS (Core-Facility Bioinformatics Integration for Multi-Omics Analyses) is a collaborative initiative involving multiple Heidelberg research core facilities, including metabolomics, proteomics, transcriptomics, spatial profiling, and deep sequencing.

The successful candidate will help build reusable bioinformatics workflows and provide computational support for integrated multi-omics research projects across the Heidelberg life science campus.

Main Responsibilities

The researcher will work on:

Developing reproducible workflows using Nextflow/nf-core

Analysing metabolomics, proteomics/phosphoproteomics, transcriptomics and spatial profiling data

Developing tools for quality control, preprocessing and statistical analysis

Performing multi-omics integration, pathway and network analysis

Creating automated reports and data visualizations

Supporting researchers with study design, analysis and biological interpretation

Contributing to publications, SOPs, training resources and funding applications

Requirements

Applicants should have:

A PhD in Bioinformatics, Computational Biology, Systems Biology, Biostatistics, Data Science or a related field

Strong programming skills in R and/or Python

Experience with reproducible computational workflows and software development practices

Experience with Nextflow/nf-core or comparable workflow systems such as Snakemake, WDL or CWL

Practical experience with at least two types of high-throughput omics data

Understanding of experimental design, batch effects and biological variation

Strong communication and collaboration skills

Excellent English; German is an advantage

Experience with Docker/Apptainer, HPC or cloud computing, multi-omics integration, pathway/network analysis, and open-source software will be an advantage.

Position Details

📍 Location: Heidelberg, Germany🏛️ Institution: Heidelberg University💼 Position: Bioinformatician (f/m/d)🔬 Area: Multi-Omics Data Analysis & Integration🗓️ Start Date: 1 January 2027⏱️ Working Hours: Full-time, 39.5 hours/week💰 Salary: TV-L E13📅 Contract: 2 years (1 January 2027 – 31 December 2028)📌 Application Deadline: 18 September 2026

Continuation beyond the initial contract may be possible depending on project development and follow-up funding.

How to Apply

Applicants should submit their application as one single PDF containing:

CV

Motivation letter

Certificates

Publication list

Contact details of referees

The application should clearly mention your experience with omics data types, statistical/integration methods, programming languages, workflow tools and relevant software. A GitHub profile can also be provided if available.

📧 Application: cos-sekretariat360@listserv.uni-heidelberg.de

Contact: Dr. Gernot Poschet — gernot.poschet@cos.uni-heidelberg.de

Official Information

For complete details and application information, applicants should refer to the official Heidelberg University job advertisement and job-market page.

Application deadline: 18 September 2026

Question 8

PhD Position in Immunometabolism – Ulm, Germany

Accepted Answer

A PhD position in Immunometabolism is available in the Fischer-Posovszky Lab, Department of Pediatrics and Adolescent Medicine at Ulm University Medical Center, Germany.

Research Project

Beyond Fat Storage: Uncovering the Immune Functions of Adipocytes

Adipocytes are increasingly understood as active endocrine and immune-regulatory cells rather than simply energy-storage cells. This PhD project will investigate how adipocytes detect pathogens, interact with immune cells, and contribute to antimicrobial host defense.

The successful candidate will study adipocyte–immune cell communication and host–pathogen interactions using human adipocyte models and modern molecular and cellular approaches.

Research Methods

The project will combine:

CRISPR/Cas9 gene editing

Cell and molecular biology

Immunological assays

Flow cytometry

Single-cell analysis

Functional assays

Human adipocyte models

The research offers an opportunity to work at the intersection of immunology, cell biology, metabolism, and host–pathogen biology.

Candidate Profile

Applicants should have an excellent Master&#8217;s degree in Biology, Molecular Medicine, Biochemistry, Biotechnology, Immunology, or a related field.

Previous experience in cell biology, molecular biology, or immunology is advantageous. The position is suited for candidates who are enthusiastic about experimental research, comfortable working in interdisciplinary teams, and have good English communication skills.

Position Details

📍 Location: Ulm, Germany🔬 Research Area: Immunometabolism & Adipocyte Immunity🎓 Position: PhD Student (m/f/d)🗓️ Expected Start: November 2026💰 Salary: TV-L E13, 65% (depending on qualification and experience)⏳ Contract: Limited🕐 Employment: Part-time📅 Application Deadline: 21 September 2026

What the University Offers

Membership in the International Graduate School in Molecular Medicine Ulm (IGradU)

State-of-the-art research facilities and core technologies

An international and collaborative research environment

Opportunities to attend international conferences

Opportunities for scientific publications

How to Apply

Applicants should submit one merged PDF file containing:

Letter of motivation

CV

Degree certificates

Academic transcripts/grade sheets for B.Sc., M.Sc., and other degrees

Applications should be sent to:

📧 Prof. Dr. Pamela Fischer-Posovszkypamela.fischer@uniklinik-ulm.de

For further information or questions regarding the position, candidates can contact the supervisor directly by email.

Application deadline: 21 September 2026

🔗 Official Job Advertisement: View the official PhD position at Ulm University Medical Center

Question 9

6 Month M2 Research Internship in Montpellier, France 2027

Accepted Answer

A 6-month Master 2 (M2) research internship is available in Montpellier, France, in 2027 for students interested in developmental biology, RNA biology, genetics, and quantitative imaging.

Research Project:

From RNA Binding to Nuclear Organisation: Dissecting Hox Transcription Factor Function In Vivo

The project aims to understand how RNA binding influences the organisation and developmental activity of Hox transcription factors.

Using an endogenous RNA-binding-deficient UbxK58A mutant in Drosophila, the research will investigate how impaired RNA binding affects:

Developmental phenotypes

RNA interactions of Ubx

Spatial organisation of Ubx in embryonic nuclei

The internship will be carried out through a collaboration between the Integrative RNA Networks in Development team at Institut de Génétique Moléculaire de Montpellier (IGMM) and the Nuclear Organization of Transcription in Embryos team at CRBM-CNRS.

The project combines developmental genetics, RNA biology, transcriptional regulation, and quantitative imaging, providing an interdisciplinary research experience for students interested in pursuing research or a PhD.

Internship Details

📍 Location: Montpellier, France🗓️ Duration: 6 months🎓 Eligibility: Master 2 (M2) students📅 Year: 2027💰 Funding: BIOLuM mini-grant programme

How to Apply

Interested students can apply by sending a CV and short motivation letter to:

📧 Julie Carnesecchi: julie.carnesecchi@igmm.cnrs.fr📧 Albert Tsai: albert.tsai@crbm.cnrs.fr

Students with an interest in developmental biology, molecular biology, RNA research, genetics, or quantitative imaging are encouraged to explore this opportunity.

Question 10

Exciting Career Opportunity: BioImaging Bioinformatician at EMBL-EBI

Accepted Answer

📋 Job Overview

Job Title: BioImaging Bioinformatician

Job Requisition ID: JR4207

Location: Hinxton, Cambridgeshire, UK

Work Type: Full-time, Hybrid

Contract Length: 18-month fixed-term (Grant-funded)

💡 About the Role & Responsibilities

You will support operational and data management development activities for the BioImage Archive and EMPIAR. A key focus will be leveraging AI approaches to optimize data processing and curation.

Data Curation & Pipelines: Support global data deposition, offer expert guidance to researchers, and build automated pipelines for complex scientific submissions.

Community Standards: Collaborate on international data standards and format developments (like OME-Zarr), and programmatically implement metadata schema languages.

Developer Liaison: Work with internal core software teams to prioritize user needs and test newly deployed archive features.

Documentation: Create high-quality technical documentation and training materials to guide global platform users.

🎓 Educational Qualifications

Minimum Requirement: A first degree (BSc) in Biology, Bioinformatics, Computer Science, or a closely related discipline, along with a relevant higher degree (MSc).

Preferred: A PhD or equivalent professional work experience in a related scientific domain.

🛠️ Required Skills & Experience

Imaging Modalities: Strong understanding of data collection, handling, and visualization for light or electron microscopy.

Programming & Scripts: Proven experience scripting data transformation pipelines using Python, Julia, or similar languages.

Data Formats: Hands-on experience with JSON exchange formats and schema validation languages like LinkML.

Personal Attributes: Strong independent and team-based problem-solving skills, curiosity for bioimaging science, and ability to meet tight deadlines.

Desirable Extras (Nice to Have):

Experience with cross-modality data like spatial transcriptomics or proteomics.

Background in bioimage analysis tools and semantic web/ontology technologies.

💰 Salary & Compensation

Base Salary: Grade 5 — Starting at £3,452.05 per month net (after tax). (Note: This excludes generous pension and insurance contributions).

Core Benefits: 30 days of annual leave, private medical/dental insurance for you and your family, and an annual salary review.

Family Support: On-site campus nursery, 10 days of child sick leave, parental leave, and monthly family/child allowances.

Campus Perks: Free commuter shuttle buses, subsidised gym and cafeteria, casual dress code, and active social/sports clubs.

International Support: Visa exemptions for international recruits, relocation packages, and education grants for private schooling.

📅 Closing Date

Deadline: Wednesday, 2nd September

Please note: Applications are reviewed on a rolling basis. Early submission is highly encouraged.

📝 How to Apply

If you are ready to apply your talent to accelerate global science, follow these steps:

Prepare an up-to-date CV and a Cover Letter outlining your transferable skills, experience, and motivation.

Head to the official EMBL-EBI recruitment portal.

Search for Job Requisition ID JR4207 to submit your documents directly through their portal.

https://embl.wd103.myworkdayjobs.com/EMBL/job/Hinxton-Cambridgeshire/BioImaging-Bioinformatician_JR4207-1

(Note: EMBL is a proud signatory of DORA and welcomes applications from all diverse backgrounds, genders, and nationalities).

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