Machine Learning Scientist – Sequence Modelling

Machine Learning Scientist – Remote Sensing

Treefera

GROW WITH TREEFERA We are a first-mile intelligence platform, delivering granular visibility into the point of origin in global ag & soft commodity supply chains - where risk, cost, performance and exposure are set. You’ll join a global, cross-functional team that values rigour, curiosity and working close to real-world challenges. Whether your focus is AI, climate, product or operations, you’ll have space to contribute meaningfully and make an impact from day one. If you’re excited by complex problems and want to help reshape how nature is valued in real-world decision-making, we’d love to hear from you. ROLE OVERVIEW Transform satellite, radar, and LiDAR signals into precise intelligence that protects forests and fortifies supply chains. You will develop models ranging from EUDR-compliant plantation mapping, to biomass estimation and forest degradation that accelerate decarbonisation and in turn enable confident, risk-adjusted decisions at global scale. WHO YOU ARE * You take models across the full lifecycle — research, prototyping, validation and productionisation — and you have shipped them in an industry, product or startup setting, not only in research. * You are fluent across the modern Python ML stack — deep learning (CNNs, U-Nets, vision transformers) in PyTorch and classical methods (gradient boosting, random forests) in scikit-learn — and you pick the right approach for the problem. * You work fluently with remote sensing data (optical and SAR) and geospatial Python tooling (rasterio, xarray, geopandas, GDAL and the STAC ecosystem), and you understand the sensor-specific quirks that matter for modelling. * You design validation that benchmarks against reference datasets, quantifies uncertainty and surfaces failure modes — and you can explain modelling choices, uncertainties and trade-offs to scientific and non-scientific stakeholders alike. * You collaborate by default across Science, Engineering and Product, bring domain exposure to deforestation, land-use change, biomass or supply-chain transparency, and have a genuine appetite for AI-assisted development workflows. Desirable requirements (if applicable): * Building on EO foundation models as a downstream substrate — lightweight classifiers, regressors or similarity search on frozen embeddings (e.g. AlphaEarth Foundations, Clay), with fine-tuning or pretraining where the case justifies it. * Multi-modal fusion across optical (Sentinel-2, Landsat), SAR (Sentinel-1, PALSAR) and LiDAR (GEDI, ICESat-2), and time-series modelling for environmental change detection (temporal transformers, sequence or self-supervised approaches). * Familiarity with STAC-based catalogues (Google Earth Engine, Microsoft Planetary Computer, AWS Open Data), AI-assisted development as a core part of your workflow, and working cross-functionally alongside solutions architects, sales and engineering. WHAT THE JOB INVOLVES * Design, train and evaluate models — from gradient boosting to CNNs, U-Nets and vision transformers — for commodity and plantation mapping, land-cover classification, change and disturbance detection, and biomass / canopy-height estimation. * Build embedding-driven workflows on top of EO foundation models — few-shot classifiers, similarity search and downstream regressors. * Design validation strategies that benchmark outputs against plot inventories and third-party reference data, quantify uncertainty and surface failure modes — producing QA artefacts (maps, plots, model cards, error analyses) that internal teams and clients can defend. * Partner with Engineering to take models into scalable, reproducible inference pipelines across millions of plots. * Contribute to a strong research culture across Science, AI and Engineering — reviewed code, shared tooling and active engagement with EO/ML literature. WHAT SUCCESS LOOKS LIKE Within 30 days you'll understand where one of our solution domains touches the ground — its data, models and the customers who rely on it. By 60 days you'll be building: an iteration of an existing model or a new MVP. By 90 days it's released, or signed off and on its way — already sharpening the intelligence organisations use to protect forests and de-risk supply chains. By six months you own a domain such as biomass, forest degradation or commodity mapping and are its point of call. Within a year you'll have shipped a next-generation solution, such as reforestation (ARR) monitoring, that moves the needle on climate-positive outcomes. WHO YOU’LL WORK WITH You'll report to Matthew Courtis and partner day-to-day with the wider Science Team, working closely with Engineering and Product. INTERVIEW PROCESS & WHAT TO EXPECT Recruiter screen (30–45 min) Hiring manager interview (45-60 min) Team & skills session (45-60 min) Final cross-functional whiteboard exercise (In person). (60 - 90 min) Accessibility: Tell us if you need adjustments, we’ll accommodate. What you’ll gain at Treefera * Build something that matters - join a high-growth climate-tech company applying AI, satellite data and quantitative modelling to real-world challenges across global supply chains, commodities and carbon. * Work on complex, meaningful problems - develop systems that balance risk, resilience, compliance and sustainability, giving organisations a genuine information advantage at global scale. * Collaborate with exceptional people - work alongside scientists, engineers and operators who are leaders in their fields, combining academic rigour with practical, cross-functional product delivery. * Ship and grow in a high-trust environment - experiment, iterate and take thoughtful risks in a team that values autonomy, creativity and continuous learning. * Develop your craft - dedicated space and time to grow your skills toward mastery, tackling technically demanding challenges that push the boundaries of applied AI and environmental data. * Be rewarded for your impact - competitive compensation, equity options, meaningful benefits, and the opportunity to help shape the future of AI-powered risk and environmental intelligence. Diversity, Equity & Inclusion Bold solutions come from diverse teams. Please refer to our DEI & EEO commitment below. If you need any accommodation during the application process, we’re here to support you. Learn more about how we think and build Many of our engineers, scientists and product leaders share their thinking publicly. Explore the Treefera blog for technical deep dives, research and product perspectives. Privacy notice By applying to Treefera, you consent to the processing of your personal data in line with our Privacy Notice. TREEFERA IS AN EQUAL OPPORTUNITY EMPLOYER. WE BELIEVE THE DIVERSITY OF OUR PEOPLE IS AS VITAL AS THE DIVERSITY OF THE ECOSYSTEMS WE WORK TO PROTECT, AND WE ARE COMMITTED TO BUILDING AN INCLUSIVE WORKPLACE WHERE EVERYONE CAN THRIVE. WE WELCOME APPLICANTS OF ALL BACKGROUNDS IRRESPECTIVE OF RACE, COLOUR, ETHNICITY, NATIONAL ORIGIN, RELIGION, GENDER IDENTITY OR EXPRESSION, SEXUAL ORIENTATION, AGE, DISABILITY, PREGNANCY, OR ANY OTHER CHARACTERISTIC PROTECTED BY APPLICABLE LAW. REASONABLE ACCOMMODATIONS ARE AVAILABLE UPON REQUEST.

Snr Data Scientist, Computational Genomics/DNA Modelling

Relation Therapeutics

ABOUT RELATION Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. THE OPPORTUNITY This is a unique opportunity for a senior data scientist to work on DNA sequence modelling, statistical machine learning, and functional genomics in support of target discovery and mechanism elucidation. You will develop and apply computational models that connect genetic variation and regulatory DNA sequence to downstream molecular phenotypes, cellular programmes, and disease biology. Embedded within the Rosalind team you will build and evaluate models that link sequence to function - including variant effect prediction,regulatory activity modelling and representation learning for genomic data. DAY TO DAY YOU WILL: * Develop and implement machine learning models for DNA sequence, regulatory elements, and genetic variation in disease-relevant contexts. * Build, evaluate and benchmark models for sequence-to-function tasks such as variant effect prediction, regulatory activity prediction, and the interpretation of non-coding disease signals. * Integrate sequence-derived representations with transcriptomic, epigenomic, and perturbational datasets to uncover disease mechanisms and support target prioritisation. * Partner closely with experimental and machine learning researchers to validate hypotheses, interpret results, and guide downstream studies. * Communicate findings clearly to internal stakeholders, including presenting methods, results, and recommendations. * Contribute to publications, scientific communications, and project documentation, supporting scientific excellence and external visibility. PROFESSIONALLY, YOU WILL HAVE * PhD in computational biology, machine learning, statistics, genomics, bioinformatics, or a related quantitative discipline. * Post-PhD experience, ideally including time in an industry, biotech, or pharmaceutical environment. * Experience with DNA language models, genomic foundation models, or transformer-based sequence models. * Understanding of statistical machine learning and probabilistic modelling, with experience selecting and evaluating appropriate modelling approaches for complex biological datasets. * Knowledge of statistical genetics methods (e.g fine-mapping, colocalisation,, or variant to gene approaches). * High proficiency in Python (preferred) and R, with experience working in high-performance computing environments. * Ability to operate independently, driving projects from concept through delivery. * Bonus experience: * Familiarity with single-cell transcriptomics or patient-derived datasets. * Experience working in interdisciplinary teams within biotech or pharma settings. * Experience integrating machine learning models with genomics, single-cell, or perturbation datasets. * Familiarity with 3D genome / chromatin interaction data where relevant (Hi-C, Capture-C, etc.). PERSONALLY, YOU: * Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams. * Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work. * Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect. * Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams. * Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes. WORKING STYLE & CULTURE AT RELATION At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! RECRUITMENT AGENCIES: Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs. Relation is a committed equal opportunities employer.

Data Scientist, Antibody Design (12-month FTC)

Relation Therapeutics

ABOUT RELATION Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. THE OPPORTUNITY Relation is offering an outstanding opportunity for a Data Scientist to support computational drug discovery and drug-ability efforts focused on antibodies. You will work closely with external deep learning–driven antibody design platforms to critically evaluate generated candidates, extract insights, and integrate learnings into internal discovery strategies. DAY TO DAY, YOU WILL * Support computational antibody discovery and drug-ability efforts across research programmes. * Work with internal and external teams to evaluate and interpret computationally generated antibody candidates. * Contribute computational and structural biology expertise to multidisciplinary project teams. * Help extract insights from sequence, structural, and modelling data to inform discovery decisions. * Collaborate with machine learning and experimental scientists to support ongoing research activities. * Contribute to the development and refinement of internal computational discovery strategies and workflows. PROFESSIONALLY, YOU WILL HAVE * A PhD in computational biology, structural bioinformatics, computational structural biology, or a related field; or a Master’s degree with equivalent industry experience. * 0–2 years of experience in biotech, pharma, or a relevant postdoctoral environment. * Experience with computational approaches for antibody design and development. * Antibody sequence and repertoire analysis. * Structural modelling of antibodies and antibody-antigen complexes. * Computational protein engineering and affinity optimisation. * Machine learning and generative modelling for antibody design. * Developability and biophysical risk assessment. * Knowledge of Python as a programming language. * Understanding of the drug discovery process. Bonus experience: * Exposure to real-world drug discovery projects * Experience with additional therapeutic modalities such as small molecules, nucleic acids, or degraders * Exposure to machine learning. PERSONALLY, YOU: * Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams. * Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work. * Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect. * Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams. * Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes. WORKING STYLE & CULTURE AT RELATION At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! RECRUITMENT AGENCIES Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs. Relation is a committed equal opportunities employer.