Remote Topological Data Analysis Jobs (NOW HIRING)

Specialised Part-Time Consulting Opportunity for Computational BiologistsWe are sharing a specialised part-time consulting opportunity for computational biologists and bioinformatics professionals with graduate-level expertise in single-cell genomics, scientific programming, and advanced computational analysis.

This role supports a research project focused on challenging computational biology problems grounded in real scientific workflows. Selected experts will design original graduate-level tasks involving single-cell RNA sequencing, trajectory inference, spatial transcriptomics, multi-omic analysis, and related computational methods, then develop reference solutions and refine tasks through iterative testing.

Key ResponsibilitiesComputational Biology Problem DesignCreate original graduate-level computational problems in bioinformatics and single-cell genomicsDevelop tasks based on realistic research workflows and biological datasetsDesign multi-step problems requiring scientific interpretation and computational reasoningCreate reproducible tasks with clearly defined inputs, expected outputs, and validation criteriaRefine task difficulty based on testing and feedbackSingle-Cell RNA-Seq AnalysisDevelop problems involving preprocessing, quality control, dimensionality reduction, clustering, and downstream analysisDesign workflows using tools such as Scanpy and related single-cell Python librariesCreate tasks involving cell-type annotation and biological interpretationEvaluate analytical choices, parameter settings, and potential failure modesIncorporate realistic edge cases encountered in single-cell datasetsTrajectory & Dynamic AnalysisCreate computational problems involving pseudotime and cellular trajectory inferenceApply tools such as scVelo to RNA velocity and dynamic-state analysisDevelop tasks requiring interpretation of lineage relationships and cell-state transitionsEvaluate assumptions underlying trajectory and velocity modelsDesign problems where multiple plausible biological interpretations must be distinguished through careful analysisSpatial TranscriptomicsDevelop problems involving spatially resolved gene-expression dataWork with tools such as Squidpy and related spatial-analysis frameworksCreate tasks involving spatially variable gene identification and neighbourhood analysisEvaluate spatial relationships between cell populations and molecular featuresDesign workflows combining imaging, expression, and spatial information where relevantMulti-Omic & Integrated AnalysisCreate problems involving integration of multiple molecular data typesDevelop workflows requiring alignment and interpretation across complementary genomic measurementsAssess batch effects, biological variation, and integration qualityDesign tasks requiring careful selection of analytical approachesEvaluate whether computational conclusions are appropriately supported by the underlying dataTopological & Advanced Data AnalysisDevelop specialised problems involving topological data analysis where relevantApply tools such as GUDHI and related computational frameworksCreate persistence-based analysis workflowsInterpret topological structure within high-dimensional biological datasetsIncorporate advanced quantitative methods where they provide meaningful biological insightScientific Programming & ValidationWrite computational problem setups, oracle functions, and solution validatorsUse Python to build reproducible scientific workflowsVerify numerical and biological correctness of expected outputsIdentify software limitations, computational edge cases, and analytical failure modesDocument assumptions, dependencies, parameters, and validation logic clearlyProblem Testing & RefinementTest computational tasks against advanced systemsDetermine whether problems require genuine scientific reasoning rather than surface-level pattern matchingIdentify tasks that are too easy, ambiguous, or computationally impracticalRefine prompts, constraints, datasets, and expected outputs to reach the intended difficultyMaintain strong standards of scientific accuracy and reproducibilityIdeal ProfileMaster's degree, PhD, or equivalent research experience in Bioinformatics, Computational Biology, Genomics, Systems Biology, or a closely related STEM disciplineStrong hands-on experience with single-cell genomics and computational biological analysisProven proficiency with one or more specialised tools such as Scanpy, scVelo, Squidpy, GUDHI, or comparable scientific softwareExperience applying these tools to real research or professional projectsStrong understanding of single-cell RNA-seq analysis, trajectory inference, spatial transcriptomics, or multi-omic integrationStrong Python programming skillsAbility to design rigorous computational problems and independently validate solutionsComfortable working in Linux and terminal-based environmentsResearch publications, open-source contributions, or substantial professional computational biology work are highly valuedExperience with scientific teaching, problem-set design, computational reproducibility, or containerised environments is advantageousEngagement DetailsPart-time independent contractor engagementFully remoteExpected commitment of at least 15–20 hours per weekFlexible scheduling based on project requirementsCompensation: $60–$90/hourWork involves computational problem design, reference-solution development, scientific validation, and iterative task refinementProjects may be extended, shortened, or concluded based on project needs and performanceWork must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third partyH1-B and STEM OPT support is unavailable for this engagementAbout the PlatformThis opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

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