BioSpace
Lead Bioinformatician
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Lead Bioinformatician
role at
BioSpace
Arinale Biosciences Incorporated
Arinale Biosciences is a biotechnology startup operating in stealth mode after having been recently spun out of one of New York City’s premier academic medical centers. Occupying a unique position at the nexus of scientific discovery and healthcare, Arinale’s platform for rapid development of paradigm‑changing therapeutics will extend the benefits of precision oncology far beyond current limitations and fundamentally improve the health of cancer patients with limited treatment options. By utilizing cutting‑edge science with an unwavering commitment to patients, we’re helping create a future where every diagnosis is clearer, every decision is more confident, and every life has a better chance/more hope.
Mission Guided by vision, powered by innovation, and grounded in compassion, we will catalyze the discovery and development of a new generation of transformative cancer therapies.
Role We are seeking a lead bioinformatician to establish robust interpretative frameworks for novel NGS‑based assays. A successful candidate will integrate with experimental and computational teams, collaborating on experimental design, data pipeline development, and conceptually lead and implement data analysis and interpretation. Ideal candidates will have a strong engineering mindset, be excited to build analysis workflows from the ground up, and enjoy the creative challenge of decoding information‑rich datasets into actionable insights.
Responsibilities
Plan, develop, and execute reusable pipelines for processing NGS data and benchmark and evaluate alternative data processing procedures.
Conceptualize, design, and implement a robust interpretation framework; identify and integrate multi‑omic data to inform data interpretation.
Generate reports/dashboards for data QC metrics and interpretive readouts.
Collaborate with experimentalists on experimental design and protocol optimization.
Communicate results (oral, written) to colleagues, collaborators, and stakeholders.
Manage and advise junior associates.
Maintain knowledge of state‑of‑the‑art methodologies and best practices.
Requirements
PhD in Bioinformatics, Computational Biology, Systems Biology, or related field.
In‑depth experience with NGS data processing (e.g., RNA‑seq, ChIP/CLIP‑seq, CRISPR screens, peak calling).
Fundamental understanding of mRNA lifecycle and associated experimental assays.
Mastery of core statistical and ML procedures for normalization, differential analysis, dimensionality reduction, and clustering.
Knowledge of statistical power analyses for experimental design.
Strong interdisciplinary communication skills.
Fluency in Unix and scripting languages (e.g., Python, R).
Experience with version‑control and writing technical documentation.
Standout Experiences
Additional postdoctoral or industry experience.
Complex (heterogeneous) data integrations for functional insights.
Factor analysis for signal decomposition (e.g., NMF, model or VAE‑based methods).
DNN or other ML methodologies for sequence‑to‑profile (coverage, expression) modeling, with a focus on de‑novo feature identification.
Specialized expertise in mRNA‑protein interactions and associated assays.
Pipeline development with a workflow language (e.g., Nextflow, Snakemake).
Advanced experimental design procedures (e.g., Bayesian optimization, AI+HITL).
Cloud computing (GCP, AWS) and/or HPC (SLURM, LSF).
Schema design and database management for cataloguing datasets.
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Research, Analyst, and Information Technology
#J-18808-Ljbffr
Lead Bioinformatician
role at
BioSpace
Arinale Biosciences Incorporated
Arinale Biosciences is a biotechnology startup operating in stealth mode after having been recently spun out of one of New York City’s premier academic medical centers. Occupying a unique position at the nexus of scientific discovery and healthcare, Arinale’s platform for rapid development of paradigm‑changing therapeutics will extend the benefits of precision oncology far beyond current limitations and fundamentally improve the health of cancer patients with limited treatment options. By utilizing cutting‑edge science with an unwavering commitment to patients, we’re helping create a future where every diagnosis is clearer, every decision is more confident, and every life has a better chance/more hope.
Mission Guided by vision, powered by innovation, and grounded in compassion, we will catalyze the discovery and development of a new generation of transformative cancer therapies.
Role We are seeking a lead bioinformatician to establish robust interpretative frameworks for novel NGS‑based assays. A successful candidate will integrate with experimental and computational teams, collaborating on experimental design, data pipeline development, and conceptually lead and implement data analysis and interpretation. Ideal candidates will have a strong engineering mindset, be excited to build analysis workflows from the ground up, and enjoy the creative challenge of decoding information‑rich datasets into actionable insights.
Responsibilities
Plan, develop, and execute reusable pipelines for processing NGS data and benchmark and evaluate alternative data processing procedures.
Conceptualize, design, and implement a robust interpretation framework; identify and integrate multi‑omic data to inform data interpretation.
Generate reports/dashboards for data QC metrics and interpretive readouts.
Collaborate with experimentalists on experimental design and protocol optimization.
Communicate results (oral, written) to colleagues, collaborators, and stakeholders.
Manage and advise junior associates.
Maintain knowledge of state‑of‑the‑art methodologies and best practices.
Requirements
PhD in Bioinformatics, Computational Biology, Systems Biology, or related field.
In‑depth experience with NGS data processing (e.g., RNA‑seq, ChIP/CLIP‑seq, CRISPR screens, peak calling).
Fundamental understanding of mRNA lifecycle and associated experimental assays.
Mastery of core statistical and ML procedures for normalization, differential analysis, dimensionality reduction, and clustering.
Knowledge of statistical power analyses for experimental design.
Strong interdisciplinary communication skills.
Fluency in Unix and scripting languages (e.g., Python, R).
Experience with version‑control and writing technical documentation.
Standout Experiences
Additional postdoctoral or industry experience.
Complex (heterogeneous) data integrations for functional insights.
Factor analysis for signal decomposition (e.g., NMF, model or VAE‑based methods).
DNN or other ML methodologies for sequence‑to‑profile (coverage, expression) modeling, with a focus on de‑novo feature identification.
Specialized expertise in mRNA‑protein interactions and associated assays.
Pipeline development with a workflow language (e.g., Nextflow, Snakemake).
Advanced experimental design procedures (e.g., Bayesian optimization, AI+HITL).
Cloud computing (GCP, AWS) and/or HPC (SLURM, LSF).
Schema design and database management for cataloguing datasets.
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Research, Analyst, and Information Technology
#J-18808-Ljbffr