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Turbo codes are sensitive to both (timing) synchronization errors and signal-to-noise ratio (SNR) mismatch. Since turbo codes are intended to work in environments with very low SNR, conventional synchronization methods often fail. This paper investigates blind symbol-timing synchronization and SNR estimation based on oversampled data frames. The technique is particularly suitable for low-rate turbo codes operating in additive white Gaussian noise at low SNR and modest data-transfer rates, as in deep space, satellite, fixed wireless, or wireline communications. In accordance with the turbo principle, intermediate decoding results are fed back to the estimator, thereby facilitating decision-directed estimation. The analytical and simulated results show that with three or more samples per symbol and raised cosine-rolloff pulse shaping, performance approaches that of systems with perfect timing and SNR knowledge at the receiver.